| Friday, September 20, 2019 | |||||||
| 09:00~18:00 | Registration | ||||||
| 18:00~20:30 | Welcome Reception | ||||||
| Saturday, September 21, 2019 | |||||||
| 08:30~09:00 | Welcome and Opening Ceremony | ||||||
| 09:00~10:00 | Keynote Speech 1: Prof. Biing-Hwang (Fred) Juang | ||||||
| 10:00~10:15 | Coffee/Tea | ||||||
| 10:15~11:15 | Keynote Speech 2: Prof. Victor C.M. Leung | ||||||
| 11:15~12:15 | Keynote Speech 3: Prof. Susanto Rahardja | ||||||
| 12:00~13:30 | Lunch Break | ||||||
| Room | A | B | C | D | P | ||
| 13:30~15:30 | SPG 01 | SPG 03 | COM 01 | COM 03 | |||
| 15:30~16:00 | Coffee/Tea | ||||||
| 16:00~18:00 | SPG 02 | SPG 04 | COM 02 | COM 04 | |||
| Sunday, September 22, 2019 | |||||||
| 09:00~18:00 | Registration | ||||||
| Room | A | B | C | D | P | ||
| 08:30~10:15 | SPG 05 | SPG 06 | SPG 07 | BSPC 01 | CPT 01 | ||
| 10:15~10:30 | Coffee/Tea | ||||||
| 10:30~12:30 | SPS 01 | SPS 02 | SPG 08 | BSPC 02 | SPG 09 | ||
| 12:30~13:30 | Lunch Break | ||||||
| 13:30~15:30 | SPS 03 | SPS 04 | COM 05 | SPG 13 | CPT 02 | ||
| 15:30~16:00 | Coffee/Tea | ||||||
| 16:00~18:00 | SPG 10 | SPG 11 | SPG12 | SPG 14 | CPT03 | ||
| 18:00~20:30 | Conference Banquet | ||||||
| BSPC: | Oral Presentation for Best Student Paper Contest track | ||||||
| SPG: | Oral Presentation for Signal Processing track | ||||||
| COM: | Oral Presentation for Communication track | ||||||
| CPT: | CPT: Oral Presentation for Computing track | ||||||
| SPS: | Oral Presentation for Special Session track | ||||||
Oral
Presentation Instructions
One of
the author shall present his paper in the conference in according to the IEEE
requirement, or the paper may not be published in IEEE Explore Digital Library
(and EI).
The
presentation is a sharing of experience and is not an examination. Delegates
shall take it easy and have a good practice is communicating his research result
in the presentation, not with any pressure at all. Delegates should not worry
the English presentation but should treat it as an oral practice and learning
process.
Oral
Presentation enable author to share their knowledge and experience with experts
and researchers. Authors should relax, just summarize the key points of the
Paper and give 10-15 minutes talk. Just like talking to your colleagues will do.
The
allocated presentation time for each paper is 15 minutes which includes the time
for questions and answer from the audiences. In general, each PPT slide
presentation takes 30 seconds, so your PPT should not have more than 30 slides.
Presenters
are required to report to their Session Chairs at least 10 minutes prior to the
start of their Session. All oral presentations must be loaded from USB into the
note-book and tested before the session. PDF, Power Point are recommended.
Movies or animations in MPEG, Windows Media, and etc., should be tested before
the session.
Keynote Speaker 1
Room: Hall
Time:
09:00~10:00,
Saturday,
September 21, 2019
Session Chair:
Jianguo Huang,
Northwestern Polytechnical University
Data-driven Methods
in Signal Processing and Communication
Georgia Institute of Technology, Georgia, USA
Abstract:
A canonical practice in solving problems in the fields of signal processing
and communication has always included, as a prerequisite condition regardless of
its explicitness, an assumption on the statistical behavior of the signal or
data that the system is dealing with. For example, in data transmission, an
additive Gaussian channel or Rayleigh fading model needs to be specified for the
system design. In quantization, the optimal quantizer is one that is designed
based on the assumed distribution of the data. These assumptions are often
inconsistent with the true conditions, resulting in suboptimal solutions. An
alternative to the above paradigm is the data-driven approach, which uses actual
data in developing the solutions without model assumptions. In this talk, we
review past (and forgotten) examples of data-driven methods and present new
applications of the approach with techniques stemming from deep learning in
several communication problems. Issues associated with the data-driven approach
in contrast to the traditional model-based methods will also be discussed.
BIOGRAPHY
Biing-Hwang (Fred) Juang
is the Motorola Foundation Chair Professor and a Georgia Research Alliance Eminent Scholar at
Georgia Institute of Technology. He is also
enlisted
as Honorary Chair Professor at several renowned universities. He had
conducted research work at Speech Communications Research Laboratory (SCRL) and
Signal Technology, Inc. (STI) in the late 1970s on a number of
Government-sponsored research projects and at Bell Labs during the 80s and 90s
until he joined Georgia Tech in 2002. Prof. Juang’s notable accomplishments
include development of vector quantization for voice applications, voice coders
at extremely low bit rates (800 bps and ~300 bps), robust vocoders for satellite
communications, fundamental algorithms in signal modeling for automatic speech
recognition, mixture hidden Markov models, discriminative methods in pattern
recognition and machine learning, stereo- and multi-phonic teleconferencing, and
a number of voice-enabled interactive communication services. He was Director of
Acoustics and Speech Research at Bell Labs (1996-2001).
Prof. Juang has published extensively, including the book “Fundamentals
of Speech Recognition”, co-authored with L.R. Rabiner, and holds nearly two
dozen patents. He received the Technical Achievement Award from the IEEE Signal
Processing Society in 1998 for contributions to the field of speech processing
and communications and the Third Millennium Medal from the IEEE in 2000. He also
received two Best Senior Paper Awards, in 1993 and 1994 respectively, and a Best
Paper Awards in 1994, from the IEEE Signal Processing Society. He served as the
Editor-in-Chief of the IEEE Transactions on Speech and Audio Processing from
1996 to 2002. He was elected an IEEE Fellow (1991), a Bell Labs Fellow (1999), a
member of the US National Academy of Engineering (2004), and an Academician of
the Academia Sinica (2006). He was named recipient of the IEEE Field Award in
Audio, Speech and Acoustics, the J.L. Flanagan Medal, and a Charter Fellow of
the National Academy of Inventors (NAI), in 2014.
Keynote Speaker 2
Room: Hall
Time:
10:15~11:15,
Saturday,
September 21, 2019
Session Chair:
Oliver Choy, Chinese University of Hong
Kong
Integrated
Networking, Caching and Computing: A Big Data Deep Reinforcement Learning
Approach
Dr. Victor C.M. Leung
Shenzhen University, Shenzhen, China
The University of British
Columbia, Vancouver, BC, Canada
Abstract: Advances in information and communications technologies have fueled a
plethora of innovations in networking, caching, and computing, which are called
upon to work together to enable better and more efficient services. In the area
of networking, software-defined networking (SDN) has attracted great interests
from both academia and industry. Another new technology called
information-centric networking (ICN) has been extensively studied in recent
years. As a new paradigm in computing, fog/edge computing has been proposed to
deploy computing resources closer to end devices. In this talk, we will present
an integrated framework that can enable dynamic orchestration of networking,
caching and computing resources to improve the end-to-end system performance. As
the complexity of the system is very high, we further present a big data deep
reinforcement learning approach to optimize resource allocation within this
framework. Future research challenges will be discussed as well.
BIOGRAPHY
Victor C. M. Leung
is a
Distinguished Professor of Computer Science and Software Engineering at Shenzhen
University. He was a Professor of Electrical and Computer Engineering and holder
of the TELUS Mobility Research Chair at the University of British Columbia (UBC)
before he became an Emeritus Professor at UBC in 2019. His research is in the broad areas of
wireless networks and mobile systems, in which he has co-authored more than 1200
refereed journal/conference papers. Dr. Leung is serving on the editorial boards
of the IEEE Transactions on Green Communications and Networking, IEEE
Transactions on Cloud Computing, IEEE Network, IEEE Access, and several other
journals. He received the IEEE Vancouver Section Centennial Award, the 2011 UBC
Killam Research Prize, the 2017 Canadian Award for Telecommunications Research,
the 2018 IEEE TCGCC Distinguished Technical Achievement Recognition Award, and
the 2018 MSWiM Reginald Fessenden Award. He co-authored papers that won the 2017
IEEE ComSoc Fred W. Ellersick Prize, the 2017 IEEE Systems Journal Best Paper
Award, the 2018 IEEE CSIM Best Journal Paper Award, and the 2019 IEEE TCGCC Best
Journal Paper Award. He is a Fellow of IEEE, the Royal Society of Canada, the
Canadian Academy of Engineering and the Engineering Institute of Canada.
Keynote Speaker 3
Room: Hall
Time:
11:15~12:15,
Saturday,
September 21, 2019
Session Chair: Jingdong Chen, Northwestern Polytechnical
University
Multi-Focus Image
Fusion with Efficient Implementation
Northwestern Polytechnical
University, Xian
Abstract: Multi-focus image fusion is becoming popular
because of its various applications such as in military surveillance,
meteorological phenomena, medical imaging and even more importantly in our
mobile apps that we use everyday. In this talk, a new multi-focus image fusion
algorithm is proposed. The algorithm is specially well suited for efficient
hardware implementation. The speed of the algorithm is significantly improved by
utilizing discrete transform and computationally simple fusion rules.
Experiments on different benchmarks demonstrate that the proposed algorithm can
reduce the fusion time by up to 99.97% compared with state-of-the-art competing
methods without compromising the fusion quality.
BIOGRAPHY
Susanto Rahardja is currently a Chair Professor at the Northwestern Polytechnical University
(NPU) under the Thousand Talent Plan of People’s Republic of China. Prior joining NPU, he was the
Director of Advanced Technology Centre at Infocomm Development Authority in
Singapore, the Head of Signal Processing Department, the Deputy Executive
Director (Research) at the Institute for Infocomm Research (I2R) as
well as a Principal Scientist II at I2R in Agency for Science,
Technology and Research, Singapore. His research interests are in multimedia
signal processing, machine learning and discrete transforms. He contributed to
the development of an audio compression technology in which the patented
technology was adopted in normative ISO/IEC international standards High
Definition – Advanced Audio Coding, in which it has been licensed to several
companies. He also contributed technologies to China Audio Video Standards
AVS-L, IEEE 1857.2-2013, high performance lossless audio coding. Dr Rahardja has
published more than 300 internationally refereed journals and conference papers
and holds more than 70 primary and secondary patents. Dr Rahardja is recipients
of numerous awards including IEE Hartree Premium Award, Singapore National
Technology Award, Tan Kah Kee Young Inventor Award (Gold), Nokia Visiting
Professor Award, ACM Recognition of Service Award, China AVS Annual Award,
A*STAR Most Inspiring Mentor Award, APSIPA Appreciation and Leadership Award and
etc. Dr Rahardja is also an active IEEE member, had served as Associate Editors
in various IEEE and Elsevier journals and General Chairs of several ACM, IEEE,
APSIPA and SPIE conferences, all in the areas of multimedia. Currently, he is
serving as Associate Editors of Elsevier Journal of Visual Communication and
Image Representation, IEEE Transactions on Multimedia and IEEE Transactions on
Industrial Electronics.
Professor Rahardja previously was an associate professor
at the Nanyang Technological University, Singapore and a professor at the
National University of Singapore. He also holds an adjunct/visiting
professor/scientist appointment at Kasetsart University in Thailand, University
of Eastern Finland, Zhejiang University, University of Malaya, Nanyang
Technological University, Institute for Infocomm Research and etc. He is a
Fellow of IEEE.
INVITED TALKS
Invited Talk 1
Room:
A
Time:
10:30~10:50,
Sunday,
September 22, 2019
Session Chair:
Hongxi Yin,
Dalian University of Technology
Enabling technologies for high-speed LED based underwater visible light
communications
Nan Chi
Key Laboratory
for Information Science of Electromagnetic Waves (MoE), Fudan University
Abstract:
Underwater optical wireless communication (UWOC) is an emerging area need to
be investigated. Nowadays, underwater visible light communication (UVLC) is
expected to act as an alternative candidate in next-generation underwater 5G
wireless optical communications for the Internet of Underwater Things (IoUT).
The challenge is that the absorption, scattering, diffraction effect and
turbulence of water medium, which can bring large attenuation and nonlinearity
penalty. Therefore, the advanced modulation formats including carrier-less
amplitude and phase modulation (CAP), orthogonal frequency division multiplexing
(OFDM) and discrete Fourier transform spread orthogonal frequency division
multiplexing (DFT-S OFDM) are needed to be applied in UVLC system. What’s more,
advanced digital signal processing algorithm such as pre/post equalization,
nonlinear compensation and other algorithms based on machine learning are
needed. In this paper, we introduce several enabling technologies for high-speed
LED based underwater visible light communication.
BIOGRAPHY
Professor Nan Chi
is with School of Information Science and Engineering, Fudan University. She
is the author or co-author of more than 300 papers and has been cited more than
2000 times. She has been awarded as the New Century Excellent Talents Awards
from the Education Ministry of China, Shanghai Shu Guang scholarship, Ten
Outstanding IT Young Persons awards of Shanghai City. Her research interests are
in the area of coherent optical transmission, visible light communication and
optical packet/burst switching.
Invited Talk 2
Room:
A
Time:
10:50~11:10,
Sunday,
September 22, 2019
Session Chair:
Hongxi Yin, Dalian University of Technology
Multi-pixel
Photon Counter and Its Application in Underwater Wireless Optical Communications
Jing Xu
Ocean College, Zhejiang University
Abstract:
Foreseeing the proliferation of underwater vehicles and sensors, underwater
wireless optical communication (UWOC) is a key enabler for ocean exploration,
with strong competitiveness in short-range bandwidth-intensive applications. The
UWOC transmission distance is severely limited by the rapid decay of light
intensity in water. Ultra-sensitive multi-pixel photon counter (MPPC) opens the
door toward designing long-reach UWOC systems.
BIOGRAPHY
Prof. Jing Xu received his BS degree in Information Engineering from the Jinan University
in 2007, and his PhD degree in Information Engineering from the Chinese
University of Hong Kong in 2011. He is a professor at Ocean College, Zhejiang
University, where he leads the Optical Communications Laboratory. He is
currently engaged in 5 research projects that are supported by NSFC and The
National Key Research and Development Program of China, as well as several other
projects. He published more than 90 papers on international journals or
conferences with a total of more than 600 citations and h-index 15, as reported
by Google Scholar. He has been Co-Chair of several international conferences and
served on some TPCs. He serves as a Topical Editor of Chinese Optics Letters
(IF:1.9, JCR Q2).
Invited Talk 3
Room:
B
Time:
10:30~10:50,
Sunday,
September 22, 2019
Session Chair:
Lamei Zhang,
Harbin Institute of Technology
Advanced Polarimetric Target
Decomposition Techniques
Bin Zou
Harbin Institute of Technology Harbin
Abstract:
Polarimetric synthetic aperture radar (PolSAR) is a well-established technique
that allows identification and separation of scattering mechanisms in the
polarization signature. PolSAR can identify the fine configuration, orientation
and composition of a target using the SAR complex images in different
polarimetric channels, and the collection of PolSAR data is less influenced by
solar illumination and weather conditions. The PolSAR related researches have
been conducted for many years and various methods have been proposed, in which
polarimetric target decomposition methods are the predominant ones. Polarimetric
target decompositions try to identify and separate the physical scattering
mechanisms from the measured PolSAR data by expressing the average mechanism in
each resolution cell as the sum of independent elements. The advanced
polarimetric target decomposition techniques can effectively represent the
scattering characteristics of the target in PolSAR data for purposes of
classification and parameter estimation.
BIOGRAPHY
Bin Zou
(M’04) received the B.S. degree in Electronic
Engineering from Harbin Institute of Technology in 1990, M.Sc. degree of space
studies from International Space University, Strasbourg, France, in 1998, and
Ph.D. degree in Information and Communication Engineering from Harbin Institute
of Technology, Harbin, China, in 2001. He is currently a professor in Department
of Information Engineering, School of Electronics and Information, Harbin
Institute of Technology (HIT).
Prof. Zou was with faculty of School of Astronautics, HIT
from 1990 to 2000. Since 2000, he has been with the faculty of School of
Electronics and Information, HIT. He was a visiting scholar in Department of
Geological Sciences in University of Manitoba, Winnipeg, Manitoba, Canada from
2003 to 2004. He was working in National University of Singapore as a research
fellow during late 2006 and early 2007.
Prof. Zou has been working on synthetic aperture radar
(SAR) data and image processing for more than 20 year. During last ten years,
his research works are mainly focused on polarimetric SAR (PolSAR) image
processing and its applications. He is also interested in other remote sensing
data processing technologies, such as polarimetric SAR interferometry, high
resolution SAR image interpretation, SAR/PolSAR simulation and remote sensing
data fusion techniques. He has supervised many research projects including
National Natural Science Foundation of China, “863” projects, etc. and has
published more 100 papers, more than 70 papers were indexed by SCI/EI.
Dr. Zou is currently a senior member of IEEE, Chair of
IEEE GRSS Harbin Chapter, Trustee of Heilongjiang Surveying, Mapping and
Geoinformation Society, China.
Invited Talk 4
Room: A
Time:
13:30~13:50, Sunday,
September 22, 2019
Session Chair:
Jie Chen, Northwestern Polytechnical University
Wei Gao, Jiangsu University
RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning
from Heterogeneous Datasets
Qing Ling
School of Data
and Computer Science, Sun Yat-sen University
Abstract: We propose a class of robust stochastic subgradient
methods for distributed learning from heterogeneous datasets at presence of an
unknown number of Byzantine workers. The Byzantine workers, during the learning
process, may send arbitrary incorrect messages to the master due to data
corruptions, communication failures or malicious attacks, and consequently bias
the learned model. The key to the proposed methods is a regularization term
incorporated with the objective function so as to robustify the learning task
and mitigate the negative effects of Byzantine attacks. The resultant
subgradient-based algorithms are termed Byzantine-Robust Stochastic Aggregation
methods, justifying our acronym RSA used henceforth. In contrast to most of the
existing algorithms, RSA does not rely on the assumption that the data are
independent and identically distributed (i.i.d.) on the workers, and hence fits
for a wider class of applications. Theoretically, we show that: i) RSA converges
to a near-optimal solution with the learning error dependent on the number of
Byzantine workers; ii) the convergence rate of RSA under Byzantine attacks is
the same as that of the stochastic gradient descent method, which is free of
Byzantine attacks. Numerically, experiments on real dataset corroborate the
competitive performance of RSA and a complexity reduction compared to the
state-of-the-art alternatives.
This is a joint
work with Liping Li, Wei Xu, Tianyi Chen, and Georgios Giannakis.
BIOGRAPHY
Qing Ling received the B.E. degree in automation and Ph.D. degree
in control theory and control engineering from the University of Science and
Technology of China, Hefei, China, in 2001 and 2006, respectively. He was a
Post-Doctoral Research Fellow with the Department of Electrical and Computer
Engineering, Michigan Technological University, Houghton, MI, USA, from 2006 to
2009 and an Associate Professor with the Department of Automation, University of
Science and Technology of China, from 2009 to 2017. He is currently a Professor
with the School of Data and Computer Science, Sun Yat-sen University, Guangzhou,
China. His current research interest includes decentralized network optimization
and its applications. Dr. Ling was a recipient of the 2017 IEEE Signal
Processing Society Young Author Best Paper Award as a Supervisor. He is an
Associate Editor of the IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT and
IEEE SIGNAL PROCESSING LETTERS.
Invited
Talk 5
Room:
B
Time: 13:30~13:50,
Sunday,
September 22, 2019
Session Chair: Fengzhong Qu, Zhejiang
University
Qunfei Zhang,
Northwestern Polytechnical University
A Fast
Proportionate RLS Adaptive Equalization for Underwater Acoustic Communications
Jun Tao
Southeast University, Nanjing, China
Abstract:
A low-complexity recursive least squares (RLS) type sparse direct adaptive
equalizer (DAE) is proposed for multiple-input multiple-output (MIMO) underwater
acoustic (UWA) communications. The underlying proportionate RLS (PRLS) adaptive
filter algorithm is motivated by the idea of proportionate updating (PU)
originated in the improved proportionate normalized least mean squares (IPNLMS)
adaptive filter scheme. To overcome the high complexity of the PRLS that is
quadratic in the filter size, a fast implementation is developed in a way
similar to the design of the stable fast transversal filter (SFTF) as a
low-complexity approximation of the standard RLS adaptive filter algorithm. The
resulting fast version of the PRLS is named the proportionate SFTF (PSFTF). The
PSFTF is then adopted to update coefficients of a linear equalizer (LE), which
was tested by experimental data collected in at-sea UWA communication trials.
Experimental results showed the PSFTF-DAE achieves faster convergence and better
performance than existing SFTF-DAE and RLS-DAE.
BIOGRAPHY
Jun Tao
is with the School of Information Science and
Engineering, Southeast University, Nanjing, China. Now he is a professor. His
research interest is in underwater acoustic communication, turbo equalization,
3G-5G baseband algorithm design and verification for ASIC. From 2011-2015 he was
a Senior Engineer, Qualcomm Inc., Boulder, CO, USA. Jun Tao has a Ph.D. in
Electrical & Computer Engineering, from the University of Missouri-Columbia.
Oral Presentation Schedule
| SPG Session 01 | |
| Room: A | |
| Time: 13:30~15:30, Saturday, September 21, 2019 | |
| Session Chair: Wei Gao, Jiangsu University | |
| Oral Session: | SPG 01-1 (Paper ID: 9141) |
| Title: | CSI-Based Wireless Localization and Activity Recognition Using Support Vector Machine |
| Author: | Kang Wu, Mengwei Yang, Chuanhui Ma and Jun Yan |
| Affiliation: | College of Communication & Information Engineering, University of Posts and Telecommunications, Nanjing, Jiangsu, China. |
| Abstract: | With the development of the information technology, human activity recognition and localization has received much attentions, since they can be utilized in many fields. In this paper, a new activity recognition and localization algorithm using channel state information (CSI) measurement is proposed. The problem of activity recognition and localization are formulated as the problem of machine learning which are solve with the support vector machine (SVM) approach. In the off-line phase, after the data normalization and principal component analysis (PCA) preprocessing of the CSI measurements, the (CSI measurement, label of activity) training data set and the (CSI measurement, position information) training data set for each activity can be formed. The SVM technique are utilized for activity based classification learning and position based regression learning. At last, the activity classification function and position regression function are obtained. In the on-line phase, after the data preprocessing of the received CSI measurements, the activity is estimated by the activity classification function at first. Then, the position regression function correspond to the estimated activity result is chosen for position estimation. Experimental results illustrated the activity recognition and localization performance of the proposed algorithm. |
| Oral Session: | SPG 01-2(Paper ID: 9171) |
| Title: | Semi-Supervised Learning Based Acoustic NLOS Identification for Smartphone Indoor Positioning |
| Author: | Xujing Bai1, Lei Zhang1,2, Tong Yang1 and Zhixin Hu1 |
| Affiliation: | 1. School of Mechanical Engineering, Chang'an University, Xi'an, Shaanxi, China; 2. State Key Laboratory of Industrial Control Technology, Zhejiang University, Xi'an, China. |
| Abstract: | A novel adaptation strategy is proposed for Acoustic Echo Cancellation (AEC). The new algorithm firstly partitions the adaptive filter into several blocks and the successive blocks with the maximum l2 norm are considered to be the active blocks. Then the coefficients of the active blocks are adapted with large update probability to ensure the identification accuracy while the zero coefficients are adapted with small update probability to decrease the number of adapting coefficients. By excluding most of the zero coefficients from adaptation, the new algorithm improves its performance in terms of convergence and computation. The simulation performed in the context of AEC demonstrates the robustness and the advantages of the new algorithm. |
| Oral Session: | SPG 01-3(Paper ID: 9025) |
| Title: | Exponentially Weighted Kernel Recursive Least P-Power Algorithm |
| Author: | Wei Gao, Pengchen Ruan, Jie Li and Tianfang Xu |
| Affiliation: | School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, China. |
| Abstract: | This paper presents a novel exponentially weighted kernel recursive least p-power (EW-KRLP) algorithm. The proposed algorithm is derived exploiting the cost function of recursive weighted least power error instead of widely used second-order statistical measure of error, achieving the good tracking ability of non-stationarity and the superior robustness in the presence of impulsive noise. Simulations demonstrate the EW-KRLP algorithm has better convergence performance than the existing kernel adaptive filtering approaches in identifying the non-stationary nonlinear system under the assumption of non-Gaussian impulsive noise modeled by the symmetric α-stable distribution. |
| Oral Session: | SPG 01-4(Paper ID: 9062) |
| Title: | A Novel Algorithm for Ship Detection in Sar Images |
| Author: | Chengkai Wang, Junfeng Wang and Xingzhao Liu |
| Affiliation: | Department of Electronic Engineering, Shanghai Jiao Tong University Department of Electronic Engineering, Shanghai, China. |
| Abstract: | The difference between targets and clutter is analyzed. Considering the emotion target’s gray intensity distribution difference compared to clutter, a novel algorithm is presented for ship detection in SAR images. First, a CFAR method is used to detect ships and wakes. In the detection, the sea clutter is modeled as a Gamma distribution, and the effects of ships and wakes are greatly reduced in the estimation of the Gamma distribution. Second, ships and wakes are distinguished according to their nonhomogeneity, because ships have larger non-uniformities than wakes. The detection performance is much better by using this algorithm. The result of real data show the effectiveness of this algorithm. |
| Oral Session: | SPG 01-5(Paper ID: 9128) |
| Title: | A Model for Quantifying Pilot’S Situation Perception Based on Attention Allocation |
| Author: | Jun Chen, Zuocheng Liu, Lei Xue, Jing Liang, Yan Tong and Shizun Sun |
| Affiliation: | School of Electronic and Information, Northwestern Polytechnical University, Xi'an, Shaanxi, China. |
| Abstract: | With the rapid development of Unmanned Aerial Vehicle (UAV) technology, the tasks that pilots need to accomplish in human-machine collaborative operations are more and more complex; the cognitive load is getting heavier and the situation awareness status is seriously affected. In order to assess the pilot’s situation awareness status, it is necessary to quantify its first level, known as situation perception. Therefore, in this paper, the SEEV attention allocation algorithm is improved based on the background of human-machine collaboration and a new model for quantifying pilot’s situation perception is established based on attention allocation. The eye movement data of subjects is also collected through specific flight simulation experiments and the situation perception of the subjects is quantified in this paper. The final experimental results show that the main information that consumes most of the subjects’ attention is the roll and attack angle information, the route map information and the aircraft attitude information which is much easier to be perceived by the subjects. The results are in compliance with the flight experimental settings and can provide data support to assess the pilot's situation awareness status in the future work. |
| Oral Session: | SPG 01-6(Paper ID: 9031) |
| Title: | Construction and Integration of under Vehicle Inspection System Based on Multi-source Sensors |
| Author: | Lu Liu, Ling Xiao and Ting-ting Liu |
| Affiliation: | Ultrasound Technology Center, Institute of Acoustics, Chinese Academy of Sciences, Beijing, China. |
| Abstract: | In order to realize the independent innovation and upgrade technology of customs and other departments, an under-vehicle inspection (UVI) system based on multisource sensors is researched and developed in this paper. The system fuses four types of sensors (camera, hyperspectral instrument, microphone, infrared meter), and is integrated into the mobile intelligent detection system platform to form an intelligent target detection system. The four types of sensors can obtain the feature information of specific objects from shape, material and structure respectively, and display them in the form of pictures. After the completion of system coordination and integration, in March 2019, the multi-source sensors UVI system was applied in the Turgart custom of Xinjiang region. In the application testing, the test tasks are better completed. The hardware and software of the system are stable, the detection speed is fast, and the recognition accuracy is high. It can effectively improve the vehicle chassis target detection ability in complex real scenes, and provide mature target detection system and solution for customs field. |
| SPG Session 02 | |
| Room: A | |
| Time: 16:00~18:00, Saturday, September 21, 2019 | |
| Session Chair: Lanjun Liu, Ocean University of China | |
| Oral Session: | SPG 02-1(Paper ID: 9149) |
| Title: | Feature Optimization Integrated with Hybrid Regression Based Machine Learning Using Received Signal Strength Measurements for Indoor Localization |
| Author: | Shengmei Liu and Xiao Yang |
| Affiliation: | College of Communication and Information Engineering, Nanjing University of Posts and Telecommunications, Jiangsu, China. |
| Abstract: | In this article, a new indoor positioning algorithm with received signal strength indicators (RSSI) fingerprints by feature optimization and hybrid regression (HR) model is proposed. In the offline phase, the gaussian filtering and normalization are utilized to pre-processing training set. Immediately after, the unsupervised clustering Kmeans ++ algorithm is applied to obtain the labels of each measurement and the measurement label set is used for classification learning by the support vector classification(SVC) method. Moreover, ReliefF(RF) and Principal Component Analysis (PCA) based feature optimization is applied to extract features from each measurement-position. Finally, HR learning is performed. In the online phase, the fingerprint scoring program (FSP) is used to assess the training set. Then, the coordinates of test points are predicted by RFPCA-HR algorithm. The field tests show that, with reducing the volume of data by about 98%, the positioning system has an average positioning error of 0.92m and the maximum positioning error is controlled within 2m. This method has a certain improvement compared with the previous methods. |
| Oral Session: | SPG 02-2(Paper ID: 9058) |
| Title: | An Improved EMD Adaptive Denoising and Feature Extraction Algorithm |
| Author: | Guifen Ren and Zengli Liu |
| Affiliation: | Kunming University of Science and Technology, Institute of information engineering and aeration, Yunnan, China. |
| Abstract: | The noise is often accompanied in the process of extracting the signal from the engineering application which will cause a large error in the processing of the signal and interferer the judgment. Aiming at this problem, this paper proposes an improved EMD adaptive removing noise and feature extraction algorithm. The method firstly uses the nonlinear non-stationary signal adaptive analysis method EMD to decompose the signal, and then selects the appropriate threshold to generate EMD decomposition. The high-frequency component is removed noise, and finally the component of removed noise is filtered by an adaptive filter and combined to generate a new signal, and then the new signal is subjected to frequency domain analysis to extract features. The effectiveness and feasibility of the proposed method are verified by simulation signals and example simulations. |
| Oral Session: | SPG 02-3(Paper ID: 9060) |
| Title: | PUVM2-Based Combined Orbit Determination Strategy for the Space Tracking Ship |
| Author: | Caifa Guo, Xuliang Wang, Yanzhen Tang and Jie Xiang |
| Affiliation: | China Satellite Maritime Tracking and Control Department, Jiangyin, Jiangsu, China. |
| Abstract: | The photoelectric theodolite is a kind of optical system which can provide much higher precision range and angle measurement in comparison with the radio devices. With the application of theodolite in satellite tracking by using the space tracking ship, a new combined orbit determination strategy is proposed which uses the range measurement of unified S band system (USB) and the angle measurement of theodolite. The improved perturbation unit vector method is applied for the initial orbit determination. The new strategy is demonstrated with the real data of a near-circular orbit China's satellite mission in 2016. With the angle measurement of theodolite, the initial orbit determination is improved greatly which show the validity of this new strategy. The strategy is tested by using multi-arc data for numerical orbit improvements as well. In the numerical method, the Adams-Cowell algorithm is used to determine the orbit elements. The precision of the orbit improvement results are at the same level by using all the measurement of USB and the new strategy. The comparison analysis shows the new strategy is more suitable for the initial orbit determination when the amount of data is small. |
| Oral Session: | SPG 02-4(Paper ID: 9002) |
| Title: | A Hybrid PSO-GA Algorithm Based Directional Modulation Technique |
| Author: | Feng Liu1, Ling Wang1, Jian Xie1 and Wei Zhang2 |
| Affiliation: | 1.Northwestern Polytechnical University, Xi'an, Shaanxi, China; 2. Northwestern University, Xi'an, Shaanxi, China. |
| Abstract: | Directional Modulation (DM) technique, as a promising mean to secure wireless communication, has been attracting increasing attention in recent ten years. The baseband modulation signal is synthesized at the antenna level for maintaining the standard constellation format along the prescribed direction while simultaneously distorting the signal constellation in other directions. In this paper, we present a novel phased DM signal synthesis method using an improved hybrid algorithm, which takes advantages of both genetic algorithm (GA) and particle swarm optimization (PSO) algorithm. The proposed DM signal has a narrower information beam-width, so it offers a better physical layer secure performance compared with the GA or PSO optimized directional modulation signal. Simulation results validate the proposed synthesis approach. |
| Oral Session: | SPG 02-5(Paper ID:9034) |
| Title: | Semi-supervised Video Object Segmentation with Recurrent Neural Network |
| Author: | Xuanguang Ren1, Han Pan1, Zhongliang Jing1 and Lei Gao2 |
| Affiliation: | 1. School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China; 2. Science and Technology on Avionics Integration Laboratory, Shanghai Jiao Tong University, Shanghai, China. |
| Abstract: | Object segmentation in videos has been extensively investigated recent years. However, semi-supervised object segmentation in videos is still a challenging research topic as it is hard to modeling temporal information. Most of research treats video frames independence and lost the relationship between adjacent frames. To overcome the limitation, we propose Semi-supervised Video Object Segmentation with Recurrent Neural Network (SVOSR) which combines convolutional gated recurrent unit (ConvGRU) to learn the temporal information between adjacent frames. The proposed method can be divided into three main parts. First, the feature extraction part is proposed to generate spatial information from adjacent frames. Second the relation part extracts temporal information from the adjacent spatial information. Thirdly, the decoder part combines the spatiotemporal information and inference the results. We put forward the relation part and design the decoder part to better segmentation. Experiments show that the proposed method shows comparable accuracy while having the order of magnitude faster runtime compared with OSVOS and other methods based on DAVIS dataset. |
| Oral Session: | SPG 02-6(Paper ID: 9195) |
| Title: | Relationship Modeling between Nitrogen Phosphorus Content and Near-infrared Spectrum of Offshore Sediments |
| Author: | Lanjun Liu1, Li Deng1, Jialin Chen1, Pingping Fan2, Caiyi Chen1 and Yongqing Zhai1 |
| Affiliation: | 1.College of Engineering, Ocean University of China, Qingdao, Shandong, China; 2. Institute of Oceanographic Instrumentation Qilu University of Technology, Qingdao, Shandong, China. |
| Abstract: | Rapid in-situ determination of total nitrogen and total phosphorus in offshore sediments is an urgent need for real-time monitoring of the marine environment. Spectral analysis technology is a commonly used non-chemical method for the determination of total nitrogen and total phosphorus in soil. Establishing a relationship model between total nitrogen (TN) and total phosphorus (TP) in offshore sediments and its spectra can effectively support its rapid in-situ determination. Therefore, this paper proposes a method to model the relationship between TN and TP in offshore seabed sediments and their visible near-infrared spectra. The modeling process includes exception sample removal, sample spectral preprocessing, sample set partition and relationship modeling. Mahalanobis distance (MD) method is used to eliminate exception samples; Savitsky-Golay (S-G) filtering, multiplicative scatter correction (MSC) and standard normal variate (SNV) are used to pre-process sample spectra; the Kennard-Stone (K-S) selection method is used for sample set partition; partial least squares regression (PLSR) is used for relationship modeling; determination coefficient (R2) and root mean square error (RMSE) are used to evaluate the modeling. Based on the 177 offshore sediments sample data collected in Qingdao offshore, using the visible near-infrared (250-950nm) spectra, the test results show that the method based on SNV and PLSR has the best performance. Based on the proposed relationship modeling process, the software for rapid determination of TN and TP in offshore seabed sediments is presented, which integrates sample spectral acquisition, sample relationship modeling and sample testing. |
| SPG Session 03 | |
| Room: B | |
| Time: 13:30~15:30, Saturday, September 21, 2019 | |
| Session Chair: Lin Cui, Xi’an Polytechnic University | |
| Oral Session: | SPG 03-1(Paper ID: 9105) |
| Title: | Success Rate Evaluation for Interferometer Ambiguity Resolving |
| Author: | Fuhe Ma, Zhang-Meng Liu, Min Zhang and Fucheng Guo |
| Affiliation: | National University of Defense Technology, Changsha, Hunan, China. |
| Abstract: | Success rate evaluation of ambiguity resolution in interferometer-based direction finding (DF) system is utmost important. In this paper, the ambiguity resolution problem is analyzed from a maximum-likelihood (ML) perspective, and the orthogonal projection is utilized to derive the expression of ambiguity resolution success rate. Due to the irregular shape of the pull-in region of successful ambiguity resolution, no closed-form expressions for this ambiguity success rate exist except the particular ternary linear array case. To cope with this, a numerical method is proposed to approximate the success rate accurately. Simulation results demonstrate the validity of our formulation about ambiguity resolution success rate. |
| Oral Session: | SPG 03-2(Paper ID: 9166) |
| Title: | Target Localization Based on Weighted Total Least Squares in Underwater Acoustic Networks |
| Author: | Ling Wang1, Xiaohong Shen1, Xi Liu1, Fei Hua1 and Haiyan Wang2 |
| Affiliation: | 1.Northwestern Polytechnical University, Xi'an, Shaanxi, China; 2. Shaanxi University of Science and Technology, Xi’an, Shaanxi, China. |
| Abstract: | Most existed target localization methods in underwater sensor networks assume that the locations of sensor nodes are accurate as references to infer target location. However, in practice especially in underwater acoustic networks, the self-localization errors are inevitable. In this paper, considering the presence of both self-localization errors and measurements noises, a target localization model using time difference of arrival is constructed and then the localization problem is formulated. In order to solve the problem, we propose a TDOA target localization algorithm based on weighted total least squares in an iterative fashion. The proposed model takes into account the prior information of measurement noise variance and self-localization error variance which improve the performance. Simulations are conducted to validate the effectiveness of the proposed method. The results show that the proposed WTLS-based target localization method has superior performance compared with the existed method. |
| Oral Session: | SPG 03-3(Paper ID: 9085) |
| Title: | Two-dimensional MUSIC Spectral Peak Search Algorithm Based on Improved Chicken Swarm Optimization |
| Author: | Lin Cui, YiXin Zhang and Yameng Jiao |
| Affiliation: | School of Electronics and Information Xi’an Polytechnic University, Xi'an, Shaanxi, China. |
| Abstract: | The two-dimensional classical multiple signal classification (MUSIC) algorithm is commonly used in the direction of arrival (DOA) estimation. However, it has a large amount of computation and slow computation when the spectral peaks are being searched. In view of these problems, an improved chicken swarm optimization (ICSO) algorithm with adaptive capability is proposed. In this scheme, the initial population is constructed by the theory of good point set, and the inertia weight is dynamically adjusted by introducing the feeding speed factor and aggregation degree factor. Finally, the inertia weight is added to the position updating formula of the hen. The experimental results indicate that the new method not only ensures the searching success rate, but also reduces the complexity of the computation. What's more, the system has a quicker convergence and a better stability. |
| Oral Session: | SPG 03-4(Paper ID: 9139) |
| Title: | A Method for Improving Three-Point Ranging Accuracy under Low SNR |
| Author: | You Shao, Fuchen Liu, Guangyin Zheng and Fuqing Jiang |
| Affiliation: | Hangzhou Applied Acoustics Research Institute, Zhejiang, China. |
| Abstract: | The commonly used cross-correlation time delay estimation method in three-point ranging does not perform well under the condition of low SNR, this article proposes an improved method for three point ranging, which try to combined generalized cross-correlation with second correlation delay estimation method and modify the time delay estimation flow path of three point ranging. Compared with the conventional three-point ranging algorithm, the new method combines the advantages of those two methods and has more steps in time delay estimation flow path. First, the three signals are pre-filtered. Next, a second correlation process is designed between the three signals to obtain two cross-correlation functions. Finally, cross-correlation is performed between the two cross-correlation functions and a final time delay is produced. With the time delay, the distance can be measured by the three-point ranging principle. Repeated simulation experiments show that the improved method has higher ranging accuracy under low SNR conditions than the traditional method. |
| Oral Session: | SPG 03-5(Paper ID: 9193) |
| Title: | A Flexible Frequency-invariant Beampattern Synthesis Method for Concentric Circular Microphone Arrays |
| Author: | Wenxia Wang and Shefeng Yan |
| Affiliation: | Institute of Acoustics, Chinese Academy of Sciences, University of Chinese Academy of Sciences Beijing, China. |
| Abstract: | This paper studies the broadband frequency-invariant beampattern synthesis problem for concentric circular microphone arrays (CCMAs) and reformulates a recently proposed accurate array response control (A2RC) algorithm in the circular harmonics domain (CHD). The new algorithm is named as CHD-A2RC. CHD-A2RC consists of two stages, the first is the CHD transformation, which is achieved by using the Jacobi-Anger expansion, the second is the accurate and flexible beampattern synthesis, which is inspired by the adaptive array principle. Compared with the existing beamforming approach for CCMAs, CHD-A2RC can design more kinds of beampatterns with low computational burdens. To validate the CHD-A2RC algorithm, two kinds of broadband beampatterns, i.e., the Chebyshev beampattern and the nonuniform sidelobe control beampattern are synthesized in the simulation section. Additionally, the white noise gains (WNGs) are calculated and the comparison of WNGs between the CCMA and the circular microphone array (CMA) validates the robustness of CCMAs on designing the desired beampatterns. |
| Oral Session: | SPG 03-6(Paper ID: 9220) |
| Title: | A Dictionary Optimization Method for Target Localization in Sensor Networks |
| Author: | Xiaoqiang Li, Jianfeng Chen, Weijie Tan, Wen Yang and Rongrong Zhang |
| Affiliation: | School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an, Shaanxi, China. |
| Abstract: | Compressed sensing method provides a new idea for multi-target localization in wireless sensor networks. However, in practical applications, due to the influence of sensor deployment and grid size, the sensing matrix may not satisfy restricted isometry property in sparse reconstruction. In order to solve this problem, this paper proposes a dictionary optimization method for target localization, which is based on equiangular non-coherent unit norm tight frame sensing matrix. The method uses a random matrix as the initial preprocessing matrix. By relaxation iterating the gram matrix and then matrix algebraic decomposition, an optimal frobenius norm tight frame is attained as the optimal sensing matrix. By preconditioning processing, the cross-correlation between the columns of the sensing matrix is reduced, which improves the estimation performance of the target localization. Simulation results show that the proposed method has better localization performance than forward-backward pursuit (FBP) method using non-optimized dictionary. |
| SPG Session 04 | |
| Room: B | |
| Time: 16:00~18:00, Saturday, September 21, 2019 | |
| Session Chair: Tian Ma, Xi’an University of Science and Technology | |
| Oral Session: | SPG 04-1(Paper ID: 9178) |
| Title: | Pedestrian detection method in vehicle video based on AMSSD |
| Author: | Chunli Wang and Jinning Bai |
| Affiliation: | School of Information Science and Technology, Dalian Maritime University, Dalian, Liaoning, China. |
| Abstract: | Pedestrian detection in vehicle video has high requirements for speed and accuracy of detection. To improve the detection speed, the underlying network of the SSD framework, the VGG-16 network, is replaced with MobileNet. In order to improve the detection accuracy of small targets, a deconvolution layer is added to this framework. With this layer, the feature map of low resolution and high semantic information with the feature map of high resolution and little semantic information is fused to increase the ability to extract the shallow feature. The VOC dataset and COCO dataset are used as the training set, and the Cityscapes dataset is used as the test set to verify the effect of the constructed framework AMSSD. The experimental results show that the proposed method can improve the detection speed and accuracy. |
| Oral Session: | SPG 04-2(Paper ID: 9046) |
| Title: | SE Block-based Single Shot Multibox Detector |
| Author: | Liuyu Hou and Yongping Xie |
| Affiliation: | School of information and communication engineering, Dalian University of Technology, Dalian, Liao Ning, China |
| Abstract: | We present SE block-based Single Shot Multibox Detector (SE-SSD), a framework that improves the accuracy of the Single Shot Detector (SSD). As a currently popular method, increasing the number of feature maps or the fusion of different feature layers can improve the performance of the deep networks. Other approaches such as DSOD can learn a good object detectors from scratch. In this paper, we introduce the“Squeeze-and-Excitation” (SE) block, and analyze how to use the SE block effectively to refine the performance of the SSD. The improved performance is enhanced by adaptively recalibrating channel-wise feature responses, then increasing the depth of convolutional layers. The proposed network explicitly models the nonlinear interactions between channels, and selectively emphasize or suppresses the informative features of different channels. Our network can achieve 82.0% m AP on the Pascal VOC 2007 test with an input size of 300×300 using Nvidia 1080Ti GPU. In addition, the result on Pascal VOC 2012 test and COCO can also achieve 76.4% mAP and 27.9% mAP resepectively. The result of proposed network outperforms the state-of-the-art methods R-FCN and SSD on each dataset. And the speed of the SE-SSD is still faster than Faster-RCNN and RFCN. The code will be open sourced with models upon publication. |
| Oral Session: | SPG 04-3(Paper ID: 9204) |
| Title: | Detail-Preserving Exposure Fusion Based on Adaptive Structure Patch Decomposition |
| Author: | Mali Yu, Wuyan Cheng, Hai Zhang and Xinyu Li |
| Affiliation: | School of Information Science and Technology, Jiujiang University, Jiangxi, China. |
| Abstract: | Exposure fusion aims at improving the overall visual quality, especially in the extremely bright and dark regions, by merging different exposure images. Structure patch decomposition based exposure fusion (SPD-EF) method can generate images with overall good visual quality without any post-processing steps. However, SPD-EF inevitably induces halo artifacts due to large local contrast. In this paper, we propose an adaptive SPD-EF, which can preserve the fine details and avoid halo artifacts. In the first step, each input image is partitioned into overlapping patches with the same size, each of which is decomposed into signal strength, signal structure, and mean intensity. In the second step, we propose to adjust the signal strength based on the local contrast and intensity, following which three components are merging separately. The qualitative and quantitative comparisons with four current state-of-the-art methods demonstrate that our method can not only remove halo artifacts, but also preserve the vivid color appearance and details. |
| Oral Session: | SPG 04-4(Paper ID: 9151) |
| Title: | Depth Image Based Object Localization Using Binocular Camera and Dual-stream Convolutional Neural Network |
| Author: | Yimei Zhang, Chaohui Wu, Mengwei Yang, Bin Kang and Jun Yan |
| Affiliation: | College of Communication & Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, China. |
| Abstract: | With the development of depth sensing devices, depth image based localization has received much attentions. In this paper, a depth image based object localization algorithm by the dual-stream convolutional neural network (CNN) is proposed. In the off-line phase, at each reference position, the grayscale image and its corresponding depth image pairs are collected by the binocular camera. The using the image preprocessing technique, the grayscale image and depth image are transformed to the three-channel images. Then, the dual-stream CNN with the shared weight coefficients are used for off-line regression learning. At last, the distance based regression model is obtained. In the on-line phase, after the preprocessing of the grayscale image and depth image, the final distance can be estimated by the distance based regression model. Experiment are carried out to evaluate the performance of the proposed algorithm. The test results illustrated that the proposed algorithm has better localization performance than traditional image approaches. |
| Oral Session: | SPG 04-5(Paper ID: 9232) |
| Title: | Research on Kinect-based Gesture Recognition |
| Author: | Tian Ma and Ming Guo |
| Affiliation: | College of Computer Science and Technology, Xi’an University of Science and Technology, Xi’an, Shaanxi, China. |
| Abstract: | In the study of gesture recognition, it is often affected by changes in illumination, complex background, and skin color interference. In response to these problems, this paper designed a Kinect-based gesture recognition method. Based on the Kinect somatosensory device, this paper collected the bone information and binary image of the human body, and combines the position of the bone points to obtain the hand image. Then, the feature of the hand image was extracted using the HOG algorithm, and the gesture image was classified using the SVM algorithm. In order to implement this method, we collected 10 digital gestures through Kinect and evaluated the method through experiments. The experimental results show that based on the Kinect somatosensory device, the HOG algorithm and the SVM algorithm can effectively and efficiently recognize gestures, which significantly improves the accuracy of gesture recognition, and the average recognition rate is as high as 98.3%. This is of great significance for the research and promotion of gesture recognition technology. |
| Oral Session: | SPG 04-6(Paper ID: 9067) |
| Title: | A Three-dimensional Image Processing Method Based on Data Layered Two-dimensional Normalization |
| Author: | Bibo Zhu, Hanlei Jiang and Weihua Cong |
| Affiliation: | Science and Technology on Sonar Laboratory, Hangzhou Applied Acoustics Research Institute, Zhejiang, China. |
| Abstract: | Three-dimensional high-resolution imaging is a new technology for long-range detection of underwater small targets. This technology enables three-dimensional mapping of targets in water, sinking and buried environments. The three-dimensional imaging sonar adopts the ultra-wideband low-frequency emission array with large glancing angle and the two-dimensional acoustic array with wide directivity reception, which effectively acquires underwater target depth dimension, navigation dimension and azimuth dimension information. The pulse compression processing, synthetic aperture tomography processing, and anti-reverberation high-resolution array processing are used to realize three-dimensional high-resolution imaging of underwater targets. However, since the underwater echoes come from different azimuths, depths, and media environments, the significant difference causes the reverberation of the target image area to be severely unbalanced, which directly affects the background brightness and feature contrast of the target image area, and ultimately increases the artificial identify the risk of errors. In this paper, A three-dimensional image processing method based on data layered two-dimensional normalization is studied. Firstly, by tracking the three-dimensional seabed interface, the distribution law of seafloor reflection echo energy in different azimuths is statistically obtained. Then, the acoustic energy attenuation loss of different geological strata is compensated. After that, the dynamic range of the three-dimensional acoustic image and the target feature contrast are improved by the two-dimensional normalization processing of the layered water and the stratum. The method has been processed and verified by experimental data, so as to achieve stable and efficient realization of 3D acoustic image background equalization and target enhancement, which has strong robustness, certain innovation and good engineering use value. |
| SPG Session 05 | |
| Room: A | |
| Time: 08:30~10:15, Sunday, September 22, 2019 | |
| Session Chair: Qing Li, Hangzhou Applied Acoustics Research Institute | |
| Oral Session: | SPG 05-1(Paper ID: 9001) |
| Title: | Coincidence of the Rao Test, Wald Test and GLRT for Radar Target Detection in Generalized Pareto Clutter |
| Author: | Jian Xue, Shuwen Xu and Penglang Shui |
| Affiliation: | National Lab of Radar Signal Processing, Xidian university, Xi’an, Shaanxi, China. |
| Abstract: | Adaptive detection of radar targets embedded in generalized Pareto clutter is studied in this paper. The generalized likelihood ratio test (GLRT) is usually adopted to design the suboptimal detector due to the existence of unknown parameters in the likelihood ratio test (LRT). However, the Rao and Wald tests have the same asymptotical performance as the GLRT and lower computation complexity than the GLRT. In addition, the heavy-tailed non-Gaussian clutter can be characterized well by the generalized Pareto model with inverse-Gamma texture. Therefore, we derive the detectors based on the Rao test and Wald test in generalized Pareto clutter respectively. It is proved that two detectors are statistically equivalent to the detector from the GLRT in generalized Pareto clutter. This result illustrates that the Rao test and the Wald test coincide with the GLRT in generalized Pareto clutter. |
| Oral Session: | SPG 05-2(Paper ID: 9084) |
| Title: | Convolutional Neural Network for Radar HRRP Target Recognition |
| Author: | Jingming Sun1,2, Junpeng Yu1,2 and Shengkang Yu1,2 |
| Affiliation: | 1. Nanjing Research Institute of Electronics Technology; 2. Key Laboratory of IntelliSense Technology, CETC, Nanjing, China. |
| Abstract: | Feature extraction is the key technique for radar target recognition based on high resolution range profiles (HRRPs). Traditional artificial feature extraction algorithms only utilize shallow architecture features, which result in the loss of information to characterize HRRP data inevitably and restrict the generalization performance of target recognition methods. Aiming at this issue, the deep learning tool is used in this study, and a new method for radar target recognition based on convolutional neural network (CNN) is proposed. By constructing a CNN model via taking advantage of the properties of HRRPs, and optimizing the CNN model parameters, the deep intrinsic attributes of targets contained in HRRPs are fully explored, so that moderate automatic feature extraction is realized, and target classification with high accuracy is accomplished. The performance of the proposed method is validated based on the simulated HRRP data, and the experimental results show the effectiveness of the proposed method. |
| Oral Session: | SPG 05-3(Paper ID: 9132) |
| Title: | Hybrid Localization Based on Time of Arrival and Phase Difference of Arrival Fusion |
| Author: | Qing Li |
| Affiliation: | Science and Technology on Sonar Laboratory, Hangzhou Applied Acoustics Research Institute, Zhejiang, China. |
| Abstract: | To locate the underwater target moving in a large area with a short trajectory, it is necessary to guarantee the positioning accuracy across the whole area. In the paper, a hybrid distributed underwater acoustic positioning system is employed. A positioning method based on time of arrival (TOA) and phase difference of arrival (PDOA) fusion is proposed. According to the statistical characteristics of the measured parameters, an optimization model is constructed based on the maximum likelihood (ML) criterion. With depth of the target estimated independently, the highly nonlinear optimization problem is solved by differential evolution (DE) algorithm. Complementary observation information is fully fused in the proposed method. Simulation results demonstrate the accuracy improvement of the proposed method throughout the observation area. Lake trial results further verify the effectiveness of the proposed method. |
| Oral Session: | SPG 05-4(Paper ID: 9051) |
| Title: | Targets Number Detection for Narrow-band Radar Based on Fractional Fourier Transform |
| Author: | Xin Xiong, Ziyue Tang, Yichang Chen, Wantian Wang, Zhenbo Zhu and Furong Cao |
| Affiliation: | Air Force Early Warning Academy, Wuhan, Hubei, China. |
| Abstract: | Based on Fractional Fourier Transform (FrFT), a targets number detection method is proposed for conventional narrow-band radar in this paper. Firstly, the fractional Fourier transform angle is estimated based on the minimum entropy criterion. And then, the narrow-band echo data are transformed to frequency domain via FrFT from the estimated angle. Finally, the sorties are identified by peak detection of the transform results. The simulation results verify the effectiveness of the proposed method. |
| Oral Session: | SPG 05-5(Paper ID: 9146) |
| Title: | Navigation Calibration Algorithm Assisted by Single Beacon |
| Author: | Juncheng Zhang, Lan Qin, Dajun Sun and Yunfeng Han |
| Affiliation: | Harbin Engineering University, Heilongjiang, China. |
| Abstract: | Autonomous underwater vehicle has become an important tool to replace human beings to complete abyssal operations and missions. As the most widely used positioning and navigation technology, inertial navigation system integrated with doppler velocity log to carry out dead reckoning exists significant shortcomings of positioning error accumulated over time. In this paper, on the background of the modification and calibration of inertial navigation drift, a positioning and navigation algorithm based on the principle of indirect adjustment is proposed, which takes single-beacon range information and velocity information as the observation quantity. This paper builds a single-beacon navigation model and analyzes its observability, as well as evaluates the positioning accuracy. The simulation analysis and lake test data processing show that the algorithm can effectively suppress the divergence of inertial navigation error and realize the AUV’s long-time high-precision navigation. |
| SPG Session 06 | |
| Room: B | |
| Time: 08:30~10:15, Sunday, September 22, 2019 | |
| Session Chair: Guiqing He, Northwestern Polytechnical University | |
| Oral Session: | SPG 06-1(Paper ID: 9157) |
| Title: | Short-Range Moving Human Detection Based-on Cascaded Spatial-Temporal Three-Stages Detector in UWB Radar |
| Author: | Runhan Bao, Zhaocheng Yang, Yige Cheng and Haifan Liu |
| Affiliation: | Shenzhen University, Shenzhen, Guangdong, China. |
| Abstract: | In this paper, we propose an cascaded spatial-temporal three-stages (CSTTS) detector for short-range human detection using mono-static ultra-wideband (UWB) radar. The key technical difficulty is how to improve the detection performance of relatively remote or slow speed targets in strong clutter environments. To solve this problem, the proposed detector can be divided into three stages: firstly, we do the outliers detection along the temporal dimension according to an adaptive updated environment clutter's maps; then we use a log-normal order-statistical constant-false-alarm-rates (OS-CFAR) detector to set a series of thresholds along the spatial dimension(i.e. different range bins);finally an accumulative detector is applied to remove a few false alarms. Experiment results show the improved performance of the proposed CSTTS detector for relatively remote and slow speed targets. |
| Oral Session: | SPG 06-2(Paper ID: 9136) |
| Title: | Convergence Analysis of Unscented Transform for Underwater Passive Target Tracking in Noisy Environment |
| Author: | Wasiq Ali1, Yaan Li1, Shujaat Ali Khan Tanoli2, Muhammad Asif Zahoor Raja2, Kashif Javaid1 and Nauman Ahmed1 |
| Affiliation: | 1.School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an, Shaanxi, China; 2. Department of Electrical and Computer Engineering, COMSATS University Islamabad, Attock, Pakistan. |
| Abstract: | Optimal passive target tracking in noisy ocean environments is an important research problem. This issue is frequently dealt with nonlinear Bayesian filtering techniques, in which passive measurements are nonlinear while the dynamic system model is considered linear. The key objective of underwater passive target tracking is to accurately estimate the motion parameters of the target from uncertain measurements extracted from array elements. In this paper, the rule of unscented transform is used to examine the convergence of unscented Kalman filter (UKF) and unscented Rauch Tung Striebel (URTS) type Kalman smoother. This study delicately finds the real-time state of a long distance dynamic target in a noisy complex underwater scenario, in which variance of background noise is high. Underwater Bearings-Only Tracking (BOT) technology is used for tracking purposes by deploying eight array elements which are localized on a horizontal Uniform Linear Array (ULA). Simulations are done for finding Root Mean Square Error (RMSE) between the actual and estimated position of the target. Independent numerical results demonstrate that URTS smoother offers a higher convergence rate from UKF in a noisy ocean environment. |
| Oral Session: | SPG 06-3(Paper ID: 9145) |
| Title: | Beamforming-based Speech Enhancement Based on Optimal Ratio Mask |
| Author: | Qiang Ji, Changchun Bao and Rui Cheng |
| Affiliation: | Speech and Audio Signal Processing Laboratory, Faculty of Information Technology, Beijing University of Technology, Beijing, China. |
| Abstract: | Speech enhancement in the noisy and reverberant environment remains a challenging task. Acoustic beamforming algorithm with minimum variance distortionless response (MVDR) has shown to be effective for this case. The crucial issue in MVDR-based speech enhancement is to get accurate estimates of the speech and noise spatial covariance matrices (SCMs). On this way, time-frequency mask-based method which is a reliable method to estimate the SCMs can improve the performance of the MVDR beamformer in speech enhancement. In this paper, an optimal ratio mask-based method used for MVDR beamforming is proposed. Specifically, the convolutional neural networks (CNNs) is used in the proposed method, which operates on the magnitude and phase components of the short-time Fourier transform (STFT) of microphones to estimate the optimal ratio masks, and these masks are used to get the SCMs for constructing MVDR beamformer. Experiments are conducted by using simulated data. The results show that the proposed method is more robust than the reference methods against the terrible acoustic conditions. |
| Oral Session: | SPG 06-4(Paper ID: 9017) |
| Title: | A 3D Audio Coding Technology Based on DRA |
| Author: | Jianxin Yan and Lei Wang |
| Affiliation: | National Engineering Laboratory for Digital Audio Coding Technology, Guangzhou, Guangdong, China. |
| Abstract: | DRA (Digital Rise Audio) is referred to specification for multi-channel digital audio coding technology which was issued as a Chinese national standard in 2008. A novel 3D audio coding algorithm based on DRA is presented in the paper with a significant improvement on the coding efficiency of DRA by BWE (Band Width Extension), MCR (Maximal Coherence Rotation) and other tools, and the subjective testing result shows the 3D audio coding technology can be applied to the UHD audio system at 256kbps and 384kbps per 5.1.4 channels plus 4 audio objects. |
| Oral Session: | SPG 06-5(Paper ID: 9229) |
| Title: | A Novel Push-To-Talk Service over Beidou-3 Satellite Navigation System |
| Author: | Yincheng Huo1, Zhen Ao1, Yuting Zhao2, Huiru Liu3 and Guiqing He1 |
| Affiliation: | 1. Northwestern Polytechnical University, Xi'an, Shaanxi, China; 2. Ningbo Maritime Networks, Com. Ltd, Ningbo, Zhejiang, China; 3. Beijing Electro-Mechanical Engineering Institute, Beijing, China. |
| Abstract: | BDS-3(Beidou Navigation Satellite System) started to provide global services since Dec 2018. The two-way SMS(short message service) of the BDS is an advantage over other satellite navigation systems. However, BDS SMS only supports text, causes inconvenience in many situations. We had developed a 300bps vocoder in 2017, which led to a 2-second voice message over BDS-1. Based on it, we used a SELP (sinusoidal excitation linear prediction) algorithm to develop a 600bps vocoder over BDS-3. Compared with the former one, voice quality has been improved from MOS 2.3 to MOS 3.5, coding delay has been increased from more than 200ms to 100ms. The voice length has been increased to 25 seconds. Our effort can offer subscribers a Push-To-Talk service over BDS. In May 2018 the novel technology has been recommended as a candidate to “International Maritime Rescue Satellite Terminal Standard”. Our efforts have very important theoretical research significance and practical reference value for BDS. |
| SPG Session 07 | |
| Room: C | |
| Time: 08:30~10:15, Sunday, September 22, 2019 | |
| Session Chair: Lianyou Jing, Dalian University of Technology | |
| Oral Session: | SPG 07-1(Paper ID: 9011) |
| Title: | Adaptive GLRT-, Rao- and Wald-Based CFAR Detectors for Distributed Targets |
| Author: | Zuozhen Wang1, Juexin Zhang2 and Zhiqin Zhao2 |
| Affiliation: | 1. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China; 2. School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China |
| Abstract: | Distributed targets detection in Gaussian noise is studied. Since the noise power is possible to change from cell to cell due to the heterogeneity of the surveillance area, the noise in the test/training data is assumed to have the same structure of covariance matrix (CM) but various powers. Three detectors are derived via the generalized likelihood ratio test, Rao and Wald tests, respectively. The new detectors have the statistical constant false alarm rate (CFAR) properties against the noise power and structure of the noise CM. Monte Carlo simulations show that the new detectors outperform their counterparts. |
| Oral Session: | SPG 07-2(Paper ID: 9048) |
| Title: | Automatically Predicting Severity of Parkinson’S Disease Using Model Based on XGBoost from Speech |
| Author: | Xuchen Zhu1, Yong Fang1 and Peng Wen2 |
| Affiliation: | 1.Shanghai University, Shanghai, China; 2. University of Southern Queensland, Queensland, Australia. |
| Abstract: | Self-service assessment model for measuring severity of Parkinson’s disease (PD) has recently received considerable attention due to the inconvenience and cost of physical visits to the medical clinic for PD patients. Previous works, however, mostly focus on the feature extraction and classifier design without considering notable intrinsic differences between patients with Parkinsonism (PWP), which has an adverse impact on generalization of model detecting PD. This paper introduces a novel PD-detected model based on Extreme Gradient Boost (XGBoost), where prior knowledge including gender and age are used to predict the severity of PD through unified Parkinson’s disease rating scale (UPDRS). Firstly, using gender and age as a prior knowledge decomposes the prediction model of UPDRS to get new sub-model. Secondly, we obtain a regressor trained by XGBoost on the respective sub-model. Finally, we can get the final prediction about UPDRS using trained model. The experimental results show that our method significantly improves performance on the remote Parkinson dataset. |
| Oral Session: | SPG 07-3(Paper ID: 9113) |
| Title: | Analysis of EEG Signals During Visual Processing: An ERP Study |
| Author: | Fetlework Tenssay1 and Hong Wang2 |
| Affiliation: | 1. School of Sino-Duch Biomedical and Information, Northeastern University, Shenyang, Liaoning, China; 2. School of Mechanical Engineering and Automation, Northeastern University, Shenyang China |
| Abstract: | Emotion is a complex, systematic and physiological behavior of the mental state. Brain function is related to perceptual processing of emotional stimuli. The current EEG study evaluated the contextual effect of the positive and negative valence emotional stimuli processing on neural oscillations by examining the neurological activities. EEG data were collected from eighteen individuals based on the international 10-20 system with a sampling rate of 1000Hz. Electrodes from the visual cortex were selected for analysis (O1, Oz and O2). Pre-processing and filtering of the raw data were done with an independent-component analysis (ICA) and time-frequency decomposition functions included in EEGLAB and ERPLAB toolbox. The ERP result confirmed that there is a difference in the reaction time between the negative and positive valences emotional stimuli when participants were experiencing different affective state. Positively valence stimuli react faster than negatively valence emotional stimuli. Three time windows, P2 (125-230ms), EPN (120-200ms) and P3 (300-650ms) were obtained and differences in amplitude and latencies were analyzed. A higher P2 amplitude and a remarkable decrease on P3 amplitude were observed at the visual cortex. The spectral power analysis shows a higher reactivity of alpha band than theta and beta bands. Nonetheless, we found a remarkable decrease in beta power for the given condition. However, beta and theta band showed a spectral change appeared laterally. As enlightened by different scholars, alpha oscillations are associated with the top-down control of visual cortex and play an important role for perception and involved in information processing during periodic cycle of the sensory information. |
| Oral Session: | SPG 07-4 (Paper ID: 9118) |
| Title: | Bottlenose dolphin echolocation clicks characteristics acquisition and analysis |
| Author: | Ling Li, Peng Du and Zhaohui Zhang |
| Affiliation: | Scientific and Technology on Underwater Test and Control Laboratory, Dalian, Liaoning, China. |
| Abstract: | Bottlenose dolphins use broadband, ultrasonic echolocation signals to search for, localize, classify, recognize and approach preys. Bottlenose dolphins demonstrate an adaptive control ability by adjusting echolocation click signal, but little is known of the manner or degree with which control. So it is very important to do some research on the characteristic analysis of the dolphin clicks and provide the support for new type underwater acoustic equipment development. In this paper, Echolocation clicks performing discrimination object tasks in order to investigate differential click signals were collected from bottlenose dolphin with established acquisition system for high frequency and broadband signals. Based on the number of the waves composing the click, the click signals fall into 5 classes that is one wave, two waves, three waves, four waves, five and above. Time-frequency characteristic and fuzzy function characteristic of the 5 classes clicks were acquired by the signal processing and analyzing. |
| Oral Session: | SPG 07-5(Paper ID: 9169) |
| Title: | Fall Detection Algorithm Based on Gradient Boosting Decision Tree |
| Author: | Yunkun Ning, Sheng Zhang, Xiaofen Nie, Guanglin Li and Guoru Zhao |
| Affiliation: | CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Research Center for Neural Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China. |
| Abstract: | This paper proposes a fall detection algorithm for wearable devices or mobile terminals. Since there is currently no complete data set for the fall of the elderly, most of the research uses young experimenters to collect data, so the data set and the difference in the terminal leads to the low accuracy of the fall detection algorithm. In order to improve the accuracy of the algorithm, this paper uses a two-level detection that combines the offline threshold method with the online GBDT (Gradient Boosting Decision Tree) to detect the fall action. According to the analysis of the final result, the sensitivity of the GBDT algorithm is 96%, the false positive rate is 2.8%, and the accuracy rate is 96%. The improved decision tree algorithm can detect the fall behavior more accurately than the decision tree. |
| SPG Session 08 | |
| Room: C | |
| Time: 10:30~12:30, Sunday, September 22, 2019 | |
| Session Chair: Meiqin Liu, Zhejiang university | |
| Oral Session: | SPG 08-1(Paper ID: 9100) |
| Title: | A Two-step 2-D DOA Estimation Algorithm Via Underwater Acoustic Vector-Sensor Array |
| Author: | Xueyan Han1,2, Meiqin Liu1,2 and Senlin Zhang2 |
| Affiliation: | 1. State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, Zhejiang, China; 2. College of Electrical Engineering, Zhejiang university, Hangzhou, Zhejiang, China. |
| Abstract: | Direction of arrival (DOA) estimation based on underwater acoustic vector-sensor array has extensive applications in the oceanic field. To realize an accurate DOA estimation with lower complexity, this paper proposes a novel method to carry out the two-dimentional (2-D) DOA estimation. Firstly, we introduce the regularized multiple focal underdetermined system solver algorithm (M-FOCUSS) to solve the jointly sparse vectors reconstruction problem to determine the grid points of true DOAs accurately. Then, we utilize Taylor series expansion to precisely approximate the steering vectors of true DOAs and achieve an accurate estimation of the off-grid errors by solving an optimization problem. Simulation results show that our algorithm is of less computational complexity but leads to a high DOA estimation accuracy |
| Oral Session: | SPG 08-2(Paper ID: 9064) |
| Title: | Learning-Aided Aircraft Detection for High-Resolution SAR Images |
| Author: | Xinhui Wang and Xue Jiang |
| Affiliation: | School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China. |
| Abstract: | The constant false alarm rate (CFAR) detection is one of the most widely utilized detection algorithms in SAR images. However, due to the complexity of the airport scene, using CFAR only cannot achieve satisfying aircraft detection. In this paper, we propose a novel framework of learning-aided aircraft detection by machine learning to overcome the issues. This framework links the classic CFAR with machine learning. While preserving the efficiency of the CFAR, the proposed method introduces machine learning to improve accuracy. Specifically, CFAR and a priori knowledge assist us quickly find the location of potential aircraft targets in the scene, which ensures the fast processing speed of framework. In machine learning, we classify the slices of potential targets and then train a classifier for identifying aircraft. Machine learning algorithms perform well on the classification problem, so the high false alarm caused by the traditional method can be smoothly suppressed. Meanwhile, machine learning algorithms improve the accuracy of the framework. Experimental results verify the significant performance of the proposed aircraft detection framework. |
| Oral Session: | SPG 08-3(Paper ID: 9078) |
| Title: | Sparse Channel Estimator via Block Ap-proximate Zero Norm |
| Author: | Yang Hu |
| Affiliation: | School of Information and Communication Engineering, Dalian University of Technology, Dalian, Liaoning, China. |
| Abstract: | The progressively increasing data rates have induced the research and application of sparse channel model. To obtain the source signal via the signal got from the terminal equipment, we expect to improve the estimation performance such as accuracy by exploiting the sparsity of the channel impulse response. Our work focuses on exploiting training signal to detect and estimate the channel. However, the classical algorithms such as greedy algorithm like Orthogonal Matching Pursuit (OMP),Least Mean Square (LMS), and even the modified Least Mean Square with approximate-zero norm, l1 norm or l2 norm as cost function, are not satisfying in the efficiency and reliability as we expected, i.e., their performances are expected better in convergent speed and bias of convergent value in our study. To design superior channel estimator, we tried 3 new adaptive algorithms called LMS integrated with Block l1;0 norm (BL10)and LMS integrated with Block l2;0 norm (BL20). Simulation in this paper will demonstrate the superiority of the proposed methods when dealing with sparse system. |
| Oral Session: | SPG 08-4(Paper ID: 9164) |
| Title: | Human Action Recognition Algorithm Based on DBPSO-SVM Classifier |
| Author: | Yunkun Ning, Sheng Zhang, Weimin Xiong, Guanglin Li and Guoru Zhao |
| Affiliation: | CAS Key Laboratory of HumanMachine Intelligence-Synergy Systems, Research Center for Neural Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China. |
| Abstract: | In the context of population aging, the study of behavior recognition algorithms for the elderly has important social significance. This algorithm is designed to distinguish between Fall Action and Activity in Daily Life (ADL), which is important for the fall protection of older people. This paper makes full use of the improved Discrete Binary Particle Swarm Optimization (DBPSO) to select the optimal feature subset and parameters to train SVM (Support Vector Machine) algorithm. Experimental results show that this method can achieve higher precision than non-optimized SVM, the improved DBPSOSVM algorithm can achieve more than 95% specificity and sensitivity for each action, especially when it comes to falls, the sensitivity is 98.44%, the specificity is 96.25%, and compared with the accuracy of 94.17% of the non-optimized SVM algorithm, there are good improvements. |
| Oral Session: | SPG 08-5(Paper ID: 9150) |
| Title: | Design and Verification of Wake-up Signal for Underwater Nodes |
| Author: | Dajun Sun, YujieOuyang, Yunfeng Han, Jucheng Zhang |
| Affiliation: | Acoustic Science and Technology Laboratory, Key Laboratory of Marine Information Acquisition and Security, College of Underwater Acoustic Engineering, Harbin Engineering University Harbin, Hei Longjiang, China. |
| Abstract: | The construction and improvement of the underwater acoustic network is the premise and guarantee for the development of the marine industry. Because the underwater nodes need to work for a long time, it is especially important to ensure that the nodes have a long standby capacity. In general, the node is in a low-power standby state waiting for a wake-up signal. When the node detects the wakeup signal, it will resume normal operation. In this paper, we propose a signal design based on the m-sequence. which can detect the hidden awakening signal in the complex environment with low SNR and small Doppler shift. Simulation and experimental data indicate that when the input SNR is as low as -11dB and the signal has a small Doppler shift, the system can still achieve a detection probability of 100% and ensure that the false alarm probability is lower than 10-6. |
| Oral Session: | SPG 08-6(Paper ID: 9102) |
| Title: | Classify Motion Model via SVM to Track Underwater Maneuvering Target |
| Author: | Jiaxin Zhang, Meiqin Liu and Zhen Fan |
| Affiliation: | College of Electrical Engineering, Zhejiang University, Hangzhou, China. |
| Abstract: | Maneuvering target tracking is one of the most important topics in marine research, and it is vital to track a target accurately. Tracking accuracy is closely related to the veracity of estimation of target’s motion model. To improve the accuracy of tracking single underwater maneuvering target, this paper brings up a new method to reduce tracking error caused by switching of motion models. A support vector machine (SVM) is used to classify current motion model of the target, then state of the target is estimated by a Kalman filter (KF) with dynamic parameters. Simulation results suggest that compared with the classical interacting multiple model (IMM), algorithm proposed in this paper leads to a more satisfactory tracking root mean square error (RMSE) no matter the target maneuvers or not. |
| SPG Session 09 | |
| Room: P | |
| Time: 10:30~12:30, Sunday, September 22, 2019 | |
| Session Chair: Xiaolong Liu, Air Force Engineering University | |
| Oral Session: | SPG 09-1(Paper ID: 9191) |
| Title: | A Method for Suppress Mutual Interference in Active Sonar System |
| Author: | Ye Yu-qi, Ding Feng, Hu peng |
| Affiliation: | Science and Technology on Sonar Laboratory, Hangzhou, China. |
| Abstract: | A method for detecting mutual interference between sources in a plurality of active sonar systems is implemented and developed. The simulation implements interference suppression method in the beam domain. In this method, the time series of matched filtering is compared with the response structure of the correlation function. Compare the differences in their response structures and use their similarity to detect interference arrival times. In the interference suppression phase, the interference signal is cut off in the beam domain and then filled with white noise that has been amplitude-evaluated to achieve interference suppression. Compared to a single matched filter, this method uses a variety of correlation function waveform information, which is a more sophisticated detection method. Simulation examples show that the method is effective. It also shows that the right removal of the interference signal at the beam-former output effectively reduces the false alarm caused by the interference. |
| Oral Session: | SPG 09-2(Paper ID: 9107) |
| Title: | Study on the Bunching Characteristics of Shock Wave in Different Structure of Discharge Electrode |
| Author: | Xiaolong Liu, Hongbing Li and Jun Li |
| Affiliation: | Air and Missile Defense College, Air Force Engineering University, Xi'an, China. |
| Abstract: | The bunching sound field model of a rotating ellipsoidal reflector in different structure of discharge electrode based on ANSYS/LS-DYNA is established in this paper. The bunching process of shock wave is simulated by LS-DYNA’s multi-material ALE method, and the bunching characteristics of shock wave is analyzed and validated through relevant experiments. The results show that the actual focus location is deviated from its geometrical focus location due to the nonlinearity of shock wave propagation and bunching process, and the shielding effect of the vertical discharge electrode to shock wave is stronger than the transverse discharge electrode, which cause less bunching gain. |
| Oral Session: | SPG 09-3(Paper ID: 9117) |
| Title: | Precision-improved Passive Localization Method in the Underwater Multipath Environment |
| Author: | Guocan Fang1, Huifang Chen1,2 and Lei Xie1,3 |
| Affiliation: | 1. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China; 2. Zhoushan Ocean Research Center, Zhoushan, China; 3. Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking, Hangzhou, China. |
| Abstract: | As a fundamental technology, localization plays a crucial role in the underwater wireless systems, which have been widely used in target tracking, disaster prevention and military domain. Due to the complicated environment in underwater, achieving the precise localization is still a challenge. In this paper, we propose a precision-improved passive localization method in the underwater multipath environment, where only anchors are clock synchronized and the effect of practical sound speed profile (SSP) is considered. In the proposed method, the underwater node to be localized employs the characteristic of direct paths and surface-reflected paths from anchors to realize the localization while the surface-reflected paths from some anchors are always undetectable. Simulation results show that the proposed localization method outperforms the localization schemes based on time difference of arrival (TDoA) and time of arrival (ToA) without ray-compensation. The performance of the proposed localization method is close to that of the localization schemes based on time of ToA with ray-compensation while ToA-based localization methods need strict clock synchronization between the underwater node and anchors. |
| Oral Session: | SPG 09-4(Paper ID: 9154) |
| Title: | An efficient fault diagnosis strategy based on SVDD and fuzzy clustering for ground-based electronic equipment |
| Author: | Cheng Wang, Huahui Yang and Chen Meng |
| Affiliation: | Measurement Engineering Department, Army Engineering University, Shijiazhuang, China. |
| Abstract: | In this paper, an efficient fault detection approach which employs the Support Vector Data Description (SVDD) and Fuzzy C-means algorithm (FCM) is proposed for ground-based electronic equipment. Firstly, the FCM method is applied to fault pattern mining in which the prior knowledge of equipment faults is difficult to be known. Then SVDD model is trained with different faults data independently for multi-classification. This fault diagnosis strategy can be used in health condition monitoring for ground-based electronic equipment. The experimental results verify its effectiveness in fault diagnosis with high accuracy and real-time performance. |
| Oral Session: | SPG 09-5 (Paper ID: 9106) |
| Title: | A Method for Evaluating the Risk of Ground Collapse in Goaf Based on Unascertained Measure |
| Author: | Xiaoxia Luo1, Zitong Wang1, Jian Fu2, Jichu Bai3, Zihan Wang1 and Yuyang Chen1 |
| Affiliation: | 1. College of Computer Science and Technology, Xi'an University of Science and Technology, Xi'an, China; 2. College of Big data, Taiyuan University of Technology, Tai Yuan, China; 3. College of Architecture and Civil Engineering, Xi'an University of Science and Technology, Xi'an, China. |
| Abstract: | Due to the many influencing factors of the risk of ground subsidence in goaf, the degree of influence of each factor is different, the relationship between factors is complex and the uncertainty is strong. Therefore, how to construct the evaluation model reasonably is the focus of this paper. The undetermined measure theory can well solve many uncertain problems affecting the ground collapse of the goaf. Therefore, based on the actual situation, this paper determines 15 influencing factors, uses entropy weight method and analytic hierarchy process to determine the combined weight, introduces the principle of confidence, establishes the risk assessment model of ground collapse in goaf based on the theory of certainty, and applies the model. In the Zhangjiatun Coal Mine Area I, the evaluation results are consistent with the actual situation. |
| Oral Session: | SPG 09-6 (Paper ID: 9112) |
| Title: | A Novel Particle Swarm Optimization Algorithm Using Orthogonal Directions |
| Author: | Wenzhen Yue, Bitao Jiang, Yao Lu, Xiaobin Li and Zhou Li |
| Affiliation: | Beijing Institute of Remote Sensing Information, Beijing, China. |
| Abstract: | The particle Swarm optimization (PSO) algorithm has been widely used in the optimization area when the problem to be optimized is non-convex and the gradient function is difficult to obtain. In this paper, a novel particle swarm optimization (NPSO) algorithm is proposed. Different from the standard PSO, in the NPSO algorithm the trajectories of the particles are limited to a set of orthogonal directions, one of which is pointed to the best position in the population. Each particle maintains its Own orthogonal directions, which are updated in several iterations. The convergence property of the NPSO algorithm is analyzed with the help of the dynamic system theory. Numerical experiments on benchmark functions show that the NPSO algorithm can locate the global optimum fast and accurately and is superior to the standard PSO algorithm. |
| SPG Session 10 | |
| Room: A | |
| Time: 16:00~18:00, Sunday, September 22, 2019 | |
| Session Chair: Yongsheng Yan, Northwestern Polytechnical University | |
| Oral Session: | SPG 10-1 (Paper ID: 9013) |
| Title: | A Fast Pencil Beam Pattern Synthesis Algorithm for Linear Array Antenna via Density Tapering |
| Author: | Shiwen Lei, Haoquan Hu, Jing Tian, Bo Chen and Pu Tang |
| Affiliation: | University of Electronic Science and Technology of China, China. |
| Abstract: | The paper addresses the problem of pencil beam synthesis for large array antenna, such as the Ku/Ka-satellite receiving antenna. For such a problem, the conventional phase-shift-only algorithm would achieve a fixed sidelobe level (SLL), for instance, the first SLL is −13:46 dB for uniform array antenna. Many algorithms based on convex technique are designed to further suppress the SLL to an expected level. However, all of those algorithms are time-consuming, especially for large array antenna system. To overcome the time-consuming disadvantage, a deterministic algorithm based on density tapering technique is proposed. The desired beam-pattern is assumed to follow a Gaussian function with its standard deviation controlling the beam. The proposed algorithm tries to generate a beam pattern as similar to the desired one as possible by optimizing the elements excitation. The solution to the optimal elements excitation has an explicit form with respect to the antenna parameters, thus can be solved in real-time. Simulations are carried out by comparing with the existed algorithms to assess the effectiveness of the proposed algorithm and some conclusions are remarked. |
| Oral Session: | SPG 10-2 (Paper ID: 9030) |
| Title: | Stripe removal method for remote sensing images based on multi-scale variation model |
| Author: | Dan Yang, Lichun Yang and Dabiao Zhou |
| Affiliation: | Jiangsu Automation Research Institute, Lianyungang, China. |
| Abstract: | Remote sensing images often suffer from severe stripe noise, which degrades image quality. In this paper, a destriping method is proposed with the multi-scale variation model on the basis of the analysis of stripe noise. First, a stripe noise model is established. Then, the multi-scale energy function is constructed with the unidirectional characteristics of stripe noise. Last, the function is optimized with the split Bregman approach, and the destriped image is obtained by the accumulation of the component in each scale. Experimental results on MODIS level 1B data show that the image quality and quantitative evaluation index can be improved. Compared with the typical destriping method, the proposed method can effectively remove stripe noise, and preserve detail information. |
| Oral Session: | SPG 10-3 (Paper ID: 9068) |
| Title: | Design and Research of Uniform Linear Array for Imaging Sonar |
| Author: | Zhiqiang Guan1, Jing Wang1, Wei Chu2 and Xiangkai Jia1 |
| Affiliation: | 1. School of Information Science and Engineering Yunnan University Kunming, China; 2. CSIC 750 Test Range, Kunming, China. |
| Abstract: | TKIS-I helmet-mounted colorful imaging sonar is a mechanical scanning single-beam sonar which has high transmission frequency up to 675 KHz and remote detection ability. Currently, there are more than two dozen of it serving the navy of China, which plays an important role in underwater training and rescuing. However, there are some inherent shortcomings such as long scanning time, low imaging efficiency and low data transmission rate. The work of this paper aims to shorten the scanning time of sonar equipment without reducing the resolution of close-range targets. According to the working environment and performance requirements of sonar equipment. This paper researches the Uniform Linear Array (ULA), and designs a reasonable array structure that can form controllable directional beam, enhance target signal and suppress interference. ULA improves the resolutions of close range targets and greatly shorten the scanning time. |
| Oral Session: | SPG 10-4(Paper ID: 9057) |
| Title: | Fuzzy clustering algorithm for automatically determining the number of clusters |
| Author: | Yangyan Hu and Zengli Liu |
| Affiliation: | Kunming University of science and technology, Information and Automation Institute, Kunming, Yunnan, China. |
| Abstract: | In the process of image segmentation based on clustering, it is necessary to manually determine the number of clusters segmented, which makes the image automation less. A fuzzy clustering algorithm is proposed to automatically determine the number of clusters. First, the similarity matrix is constructed using the features of the extracted image, and the number of clusters is determined using the AP clustering algorithm. Then, the obtained number of clusters is input to the FCM algorithm, and the clustering center is optimized using the firefly algorithm. Finally, a simulation experiment was conducted. The experimental results show that the improved FCM algorithm has a good effect and can realize automatic image segmentation. |
| Oral Session: | SPG 10-5 (Paper ID: 9086) |
| Title: | Space Debris Tracking Via Generalized Labeled Multi-Bernoulli Random Finite Sets |
| Author: | Sun Quan1, Ding Ding2 and Niu Zhaodong1 |
| Affiliation: | 1. National Key Laboratory of Science and Technology on ATR, College of Electronic Science and Technology National University of Defense Technology, Changsha, China; 2. Center for Teaching and Research Service National University of Defense Technology, Changsha, China. |
| Abstract: | In this paper we present an algorithm for detection and tracking space debris under complex space background via δ-generalized labeled multi-Bernoulli (δ-GLMB) random finite sets (RFS). It includes two parts, position extractor for suspected targets and tracking filter. The core strategy of this position extractor is morphological method. The filter is implemented by Sequential Monte Carlo (SMC) method and each iteration of δ-GLMB multi-target tracking filter includes two operations: update and prediction. The processing results of measured data show that the algorithm has strong detection and tracking ability for dim and small targets under complex space background. To the best of our knowledge, this is the first time that the δ-GLMB multitarget tracking filter has been successfully applied in the field of space debris target detection and tracking. |
| Oral Session: | SPG 10-6 (Paper ID: 9137) |
| Title: | Semantic Enrichment for Rooftop Modeling using Aerial LiDAR Reflectance |
| Author: | Tan Tan1, Ke Chen2, Weisheng Lu1 and Fan Xue1 |
| Affiliation: | 1. Department of Real Estate and Construction, The University of Hong Kong, Hong Kong SAR; 2. School of Civil Engineering and Mechanics Huazhong University of Science and Technology Wuhan, China. |
| Abstract: | As demanded by smart city applications, the recognition and enrichment of urban semantics from unstructured spatial big data became an emerging trend for the development of building information model (BIM) and city information model (CIM). Rooftop constructs the essential part of BIM and CIM and loads various new application practices and scenarios. The recognition and enrichment of rooftop elements represent the trending requirements. This study develops a new approach for semantic enrichment of aerial Light Detection and Ranging (LiDAR) point clouds. In this paper, machine learning models such as decision tree are applied to predict green roof elements based on the geometry and laser reflectance, and was validated in a pilot zone in the main campus of The University of Hong Kong. The recognized rooftop elements could provide a solid foundation for further research, such as rooftop landscape, rooftop energy, rooftop farming. |
| SPG Session 11 | |
| Room: B | |
| Time: 16:00~18:00, Sunday, September 22, 2019 | |
| Session Chair: Jianfeng Chen, Northwestern Polytechnical University | |
| Oral Session: | SPG 11-1(Paper ID: 9039) |
| Title: | Research on Decision-making System of Cognitive Jamming against Multifunctional Radar |
| Author: | Bokai Zhang1 and Weigang Zhu2 |
| Affiliation: | 1. Department of Postgrade Management, Space Engineering University, Beijing, China; 2. Department of Electronic and Optics Engineering, Space Engineering University, Beijing, China. |
| Abstract: | Aiming at the problem that traditional decision-making system of jamming is difficult to apply to modern warfare due to the rapid development of multifunctional radar and cognitive electronic warfare, a decision-making system of cognitive jamming against multifunctional radar is studied. Firstly, the paper takes multifunctional radar as the combat object, and analyses its working mode under search mode and tracking mode and their transformation, which provides theoretical basis and foundations for the research of decision-making system of cognitive jamming. Secondly, the shortcomings of traditional decision-making system of jamming are analyzed. Combined with cognitive thought, the decision-making system of cognitive jamming is proposed. Subsequently, the construction and update of jamming case library in the system is introduced. Finally, the basic principles of reinforcement learning and deep reinforcement learning and their applications in decision-making system of cognitive jamming are analyzed. |
| Oral Session: | SPG 11-2(Paper ID: 9143) |
| Title: | Research on Cooperative Localization Algorithm for Multi-AUV System Based on Distance Measurement |
| Author: | Jucheng Zhang, Yu Feng, Yunfeng Han and Dajun Sun |
| Affiliation: | Harbin Engineering University, Heilongjiang, China. |
| Abstract: | Multi-AUV system have becoming importance components in many tasks, such as underwater environmental monitoring and underwater mineral exploration, target detection and seabed topographic mapping. Aiming at depending on less AUV excessively and the high computational complexity caused by the increase of AUV in multi-AUV system, a cooperative localization method for multi-AUV system based on adjustment with conditions is proposed in this paper. Distance between each AUV can be measurement by underwater acoustic communication. The relative position of each AUV can be estimated by adjustment with conditions method. Simulation results show that the method can significantly improve the localization ability of whole system and lower the error compared with geometric solution method. |
| Oral Session: | SPG 11-3(Paper ID: 9042) |
| Title: | An Improved Active Sonar Automatic Tracking Method using Spatial Smoothing and PHD Filtering |
| Author: | Shao Pengfei, Wang Jun and Gu Xinyu |
| Affiliation: | Science and Technology on Sonar Laboratory, Hangzhou Applied Acoustics Research Institute, Hangzhou, China. |
| Abstract: | For monostatic pulsed active sonar detection performance decreased under strange waters where targets and interferences were unknown. This paper proposed a pre-test automatic tracking method, on the one hand, by using spatial smoothing to extract targets' spatial continuity characteristics and reduce impact of random clutter, and on the other hand, by using probability density hypothesis (PHD) filtering to further filter out the clutter, at the same time output the estimation of underwater targets' state and number, and thus help to reduce detection false alarm rate and miss rate, improves performance of the active sonar actual use. In this paper, an improved active sonar automatic tracking framework is presented, and the method is verified by sea trial data. |
| Oral Session: | SPG 11-4(Paper ID: 9162) |
| Title: | G-CRLB Analysis for Target Localization in Through-the-wall Radar |
| Author: | Lei Qiu, Wei Qu, Hongfeng Pang and Jun Yang |
| Affiliation: | Space Engineering University, Beijing, China. |
| Abstract: | Cramer-Rao lower bound (CRLB) is the optimal performance indicator for unbiased estimator. In through-the-wall target localization, the non-line-of-sight (NLOS) propagation caused by wall effect is the main factor that influences the localization performance. Based on the signal transmitting model, the NLOS is only determined by wall thickness and dielectric constant. In this paper, we use generalized Cramer-Rao lower bound (G-CRLB) as a fundamental tool to analyze the performance of target localization. We deduced the G-CRLB of target localization behind wall. The Fisher information matrix of the G-CRLB is divided into two parts: the observation matrix and prior information matrix, and the former corresponding to the measuring error, while the latter corresponding to wall parameter error. Simulation results evaluated the effect of wall parameters and measuring error on G-CRLB qualitatively. |
| Oral Session: | SPG 11-5 (Paper ID:9142) |
| Title: | Speech Enhancement Integrating the MVDR Beamforming and T-F Masking |
| Author: | Jinru Zhu, Changchun Bao and Rui Cheng |
| Affiliation: | Speech and Audio Signal Processing Laboratory, Faculty of Information Technology Beijing University of Technology, Beijing, China. |
| Abstract: | In this paper, a multi-channel speech enhancement method with the minimum variance distortionless response (MVDR) beamforming method based on the time-frequency (T-F) masking is proposed. In this study, First, the logarithmic power spectrum (LPS) features of multichannel signals are used as input features to estimate a T-F mask of the reference microphone by the deep neural network (DNN) model. Then, the estimated mask is utilized to calculate speech covariance matrix that is used to estimate a steering vector for constructing the MVDR beamformer. The steering vector is estimated by the generalized eigenvalue decomposition (GEVD) method. Finally, the output speech of the beamformer is processed by the DNN-based IRM model. In order to prove the effectiveness of the proposed method, the perceptual evaluation of speech quality (PESQ) and the segment signal-to-noise ratio (SSNR) are employed. The experimental results show that the proposed method effectively increased the PESQ and SSNR. |
| Oral Session: | SPG 11-6 (Paper ID: 9144) |
| Title: | Language Model Based Non-speech Recognition Method |
| Author: | Qinglin Zhang, Jianfeng Chen and Jisheng Bai |
| Affiliation: | School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, China. |
| Abstract: | Language model is an essential technology in natural language processing systems. Non-speeches are supposed to have some similarities to speeches and other kinds of natural languages which means that language model can be used in the field of non-speech recognition to improve the accuracy of it. In this paper, we define the semantics, grammar and context and set up a new recognition method for non-speeches by learning the order and logical relationships of different non-speeches in certain scenes to improve the recognition results. Applying this theory, the relationship between different non-speeches in certain scenes will be explored and applied to help the recognition systems, and the research on non-speeches will shift from single sound segments to the entire scenes as well as sound elements of them. |
| SPG Session 12 | |
| Room: C | |
| Time: 16:00~18:00, Sunday, September 22, 2019 | |
| Session Chair: Wang Ye, Hangzhou Applied Acoustic Research Institute | |
| Oral Session: | SPG 12-1(Paper ID: 9165) |
| Title: | An Optimal Algorithm of Time Resource for Multi-Target Tracking under Active Oppressive Jamming |
| Author: | Tingbao Tao1, Gong Zhang1 and Henry Leung2 |
| Affiliation: | 1. College of Electronic Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China; 2. Department of Electrical and Computer Engineering, University of Calgary, Calgary, Canada. |
| Abstract: | Phased-Array Radar (PAR) beam pointing is flexible, enabling rapid scanning without inertia, showing obvious advantages in dealing with complex electromagnetic environments and multitasking. In this paper, the multi-target tracking time resource optimal allocation of PAR under active oppressive jamming is studied. The Bayesian Cramer-Rao Lower Bound (BCRLB) of target location estimation is used as the allocation criterion, and a resource allocation algorithm is proposed. This algorithm can track more targets and improve tracking performance at the same time. Numerical simulations lastly validate the effectiveness of the proposed algorithm. |
| Oral Session: | SPG 12-2(Paper ID: 9019) |
| Title: | An Interpolated Iterative Adaptive Approach for Scanning Radar Imaging |
| Author: | Xiaoqing Jiang, Yueli Li, Chongyi Fan and Xiaotao Huang |
| Affiliation: | College of Electronic Science and Technology, National University of Defence Technology, Changsha, Hunan, China. |
| Abstract: | Angular superresolution has been widely applied to improve cross-range resolution for forward-looking scanning radar imaging. However, in the cases of low azimuth sampling rate, traditional methods fail to estimate off-grid targets accurately because of a lack of enough samples. Since the off-grid samples can be considered as missing data, off-grid samples could be reconstructed by exploiting the spectral characteristics of radar antenna patterns. Thus, an interpolated iterative adaptive approach (IAA) combined with spectral windowing is proposed to estimate off-grids targets as well as suppress high frequency noise. Simulation and experimental results have demonstrated higher angular resolution and positioning accuracy than traditional methods. |
| Oral Session: | SPG 12-3(Paper ID: 9037) |
| Title: | An Autofocus Imaging Method of One-Stationary Bistatic Synthetic Aperture Radar |
| Author: | Leping Chen, Daoxiang An and Xiaotao Huang |
| Affiliation: | College of Electronic Science and Technology, National University of Defense Technology, Changsha, China. |
| Abstract: | Since the trajectory deviations of the platform cause serious phase errors that degrade the focusing quality of synthetic aperture radar (SAR) imagery, an autofocus method is important for airborne SAR imaging. When it comes to one-stationary bistatic SAR (OS-BiSAR), autofocus problems become more complicated. Traditional autofocus methods make the assumption that a Fourier transforms relationship exists between the image domain and the range-compressed phase history domain, which is invalid in OS-BiSAR imaging. Based on maximum image sharpness criterion, an autofocus backprojection method is proposed. Its performance has been demonstrated by using the P-band airborne BiSAR experimental data. |
| Oral Session: | SPG 12-4(Paper ID: 9217) |
| Title: | Joint Sparse with Generalized Orthogonal Matching Pursuit for Off-Grid Wideband DOA Estimation |
| Author: | Xingchen Liu1, Haiyan Wang2, Xiaohong Shen1, Haitao Dong1 and Haixia Jing1 |
| Affiliation: | 1. School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an, Shan'xi, China; 2. School of Electronic Information and Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an, Shan'xi, China. |
| Abstract: | Off-Grid wideband DOA estimation under low signal-to-noise ratio (SNR) and limited snapshots is a challenging problem for sonar array signal processing. In this paper, we proposed a novel joint sparse method with Generalized Orthogonal Matching Pursuit (J-GOMP). The method is on the basis of classical OMP with a double steering model parameters optimization. With the chosen of K terms in the largest absolute value of the inner product, the J-GOMP algorithm can achieve faster convergence speed. The detailed algorithm realization steps are given. Simulations are conducted in comparison with classical MUSIC and OMP algorithms. The results show the proposed JGOMP has better resolution performance under low SNR with a single snapshot. |
| Oral Session: | SPG 12-5 (Paper ID: 9041) |
| Title: | Direction of Arrival Estimation Based on Improving Signal Spatial Correlation |
| Author: | Wang Ye 1, 2, Chen Tuo1 and Sun Chao2 |
| Affiliation: | 1. Hangzhou Applied Acoustic Research Institute, Hangzhou, China; 2. School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an, China. |
| Abstract: | The acoustic signal propagation in underwater channels at long ranges will cause a loss in signal spatial correlation and lead to decrease in array processing gain. In this paper, the direction of arrival (DOA) estimation algorithm based on sparse reconstruction is studied. Compared to the conventional beamforming, the signal spatial correlation is simulated to be improved throughout the process of reconstruction and the DOA is accurately estimated. The algorithm is also effective in the presence of badly attenuated signal. |
| Oral Session: | SPG 12-6 (Paper ID: 9075) |
| Title: | Targets Number Detection for Wideband Radar Based on Two-Dimensional Sparse Structure Model |
| Author: | Yichang Chen, Yuanpeng Zhang, Wantian Wang, Le Zhou, Yanwu Zhu and Xin Xiong |
| Affiliation: | Air Force Early Warning Academy, Wuhan, China. |
| Abstract: | A targets number detection method for conventional wide-band radar is proposed in this paper. Firstly, the echo signals received by radar at different slow-time are viewed as multiple measurement vectors (MMV) model. Based on the MMV model, the target echo sparse 2D spectrum in range-azimuth domain is reconstructed by simultaneous orthogonal matching pursuit (S-OMP) algorithm. Then, the detection threshold is determined according to the signal-to-noise ratio, and the binary spectrum of the echo data is obtained under this threshold. Finally, the target sorties are identified in the spectrogram by using the method of area labeling. Experimental results based on both simulated and real data demonstrated that the proposed method utilizes the two-dimensional information of the target and can improve the accuracy of sorties recognition. In addition, the proposed method and can realize the target sortie recognition from under-sampled echo data. |
| SPG Session 13 | |
| Room: D | |
| Time: 13:30~15:30, Sunday, September 22, 2019 | |
| Session Chair: Bo Chen, Xidian University | |
| Oral Session: | SPG 13-1 (Paper ID: 9072) |
| Title: | Radar HRRP Target Recognition with Target Aware Two-Dimensional Recurrent Neural Network |
| Author: | Jiaqi Liu, Bo Chen, Wenchao Chen and Yang Yang |
| Affiliation: | National Laboratory of Radar Signal Processing, Xidian University, Xi’an, China. |
| Abstract: | In this paper, a Target Aware Two-Dimensional Recurrent Neural Network (TATDRNN) is proposed for High-Resolution Range Profile(HRRP) based Radar Automatic Target Recognition(RATR), which characterizes the temporal dependence across the range cells within the single HRRP. Specifically, in our proposed TATDRNN, a Two-Dimensional RNN is introduced to model target region and noise region of HRRP data separately and a beyesian generative model is defined to separate target region and noise region according to their distribution character. Experimental results based on measured data demonstrate that our proposed TATDRNN achieves competitive recognition performance compared with traditional methods. |
| Oral Session: | SPG 13-2 (Paper ID: 9059) |
| Title: | Radar high-resolution range profile target recognition with hyperparameter self-learning |
| Author: | Yingqi Liu, Bo Chen, Wenchao Chen and Qianru Zhao |
| Affiliation: | National Laboratory of Radar Signal Processing, Xidian University, Xi’ an, China. |
| Abstract: | A hyperparameter self-learning method is developed for radar high-resolution range profile (HRRP) target recognition, which searches for the best hyperparameters based on the current data for preprocessing and feature extraction. Exploring the correlation between hyperparameters, our method achieves the optimum of parameter collocation with reinforcement learning. Experimental results on the measured HRRP demonstrate that the proposed method can attain better performance with automatic hyperparameter selection. |
| Oral Session: | SPG 13-3 (Paper ID: 9016) |
| Title: | Power-of-Two Quantizer FLANN Filter for Nonlinear Active Noise Control |
| Author: | Lu Lu1, Zongsheng Zheng2 and Xiaomin Yang1 |
| Affiliation: | 1. College of Electronics and Information Engineering, Sichuan University, Chengdu, China; 2. School of Electrical Engineering, Southwest Jiaotong University, Chengdu, China. |
| Abstract: | In this paper, a new nonlinear active noise control (NANC) algorithm that combines the filtered-s least mean square (FsLMS) algorithm and the power-of-two quantizer (PTQ), is proposed for the functional link artificial neural network (FLANN) based NANC system. With a moderate increase in computational complexity, the proposed PTQ-FsLMS algorithm can significantly improve the performance of the existing algorithms in the Gaussian and α-stable noise scenarios. Moreover, the proposed algorithm is extended to deal with the multichannel NANC task. Simulation results in the context of NANC demonstrate the effectiveness of the proposed algorithm. |
| Oral Session: | SPG 13-4 (Paper ID: 9121) |
| Title: | An improved Indoor Navigation Method based on Monocular Vision Measuring and Region Based Convolutional Network |
| Author: | Li Guanqi1, Xu Haowei2 and Li Chenning3 |
| Affiliation: | 1. University of electronic science and technology of china, Chengdu, China; 2. Northwestern Polytechnical University Xi’an, China; 3. Xi'an Guide Technology Co., Ltd, Xi’an, China. |
| Abstract: | As modern architectural structures have become more and more complicated, indoor navigation is getting increasingly important. The indoor objects-based positioning algorithm is a novel indoor positioning solution, which locates the users by taking images indoor, recognizing objects, extracting related information and matching with digital maps. However, Tedious surveying work in the process of pre-layout, high computational complexity and a trend of divergence on linear solutions still restricts the performance of the method. Thus, this paper proposes an improved indoor navigation method based on monocular vision measuring and Region-based Convolutional Network(RCNN), improving the efficiency by converting the two-dimensional spatial structure presented in the photo into three-dimensional space and thereby improving the success rate of indoor positioning In order to verify the performance of the proposed algorithm, a test is conducted inside a typical structure. The result shows that comparing with the former algorithm, the proposed method provides 9.5% higher success rate at 61.9% with 92.9% fail safe rate. |
| Oral Session: | SPG 13-5 (Paper ID: 9156) |
| Title: | Sleep Anomaly Events Detection Based on Adaptive Double Threshold CFAR Detector Using UWB Radar |
| Author: | Yige Cheng, Zhaocheng Yang, Dongcai Hong and Jiongzhang Chen |
| Affiliation: | Guangdong Key Laboratory of Intelligent Information Processing, College of Electronics and Information Engineering, Shenzhen University, Shenzhen, Guangdong, China. |
| Abstract: | Detection of sleep anomaly events, such as get up, sit up and turn over, is one of the most important tasks in human sleep monitoring. In this paper, we propose a novel sleep anomaly events detection algorithm based on an adaptive double threshold constant-false-alarm-rate (ADT-CFAR) detector using ultra-wideband (UWB) radar. The proposed algorithm firstly removes the static clutter, detects the human and performs the time-frequency transform for the received signals. By extracting the power burst curve (PBC) from the obtained time-frequency maps, we can formulate the sleep anomaly events detection by a binary hypothesis test and then develop an ADT-CFAR detector, which is based on log-normal distribution. A series of experiments are conducted and the results show the effectiveness of the proposed detector. |
| Oral Session: | SPG 13-6 (Paper ID: 9234) |
| Title: | Research and Implementation of Orderly Statistical Constant False Alarm Detector |
| Author: | Haixia Yu, Liqiang Diao, Shaojuan Xu, Xinjing Qin and Guokai Huang |
| Affiliation: | City College, Dalian University of Technology, Dalian, Liaoning, China. |
| Abstract: | Radar target false alarm detection principle under the Sea clutter environments is discussed first. In this paper, we analyze the performance of the CFAR (Constant False Alarm Rate) on adaptive threshold, the CA-CFAR (Cell Averaging Constant False Alarm Rate) and OS-CFAR (Order Statistic Constant False Alarm Rate) in Rayleigh clutter assumption background. We put forward an improved MOSCA-CFAR (Mean of OS and CA-CFAR) algorithm. The performances of these detectors are compared with Matlab simulation, and the results show that MOSCA-CFAR detector in the presence of interfering targets performs better especially with the anti-interference ability and false alarm control capability. This paper designs an Ordered Statistical Constant False Alarm Rate processor with the FPGA (Field Programmable Gate Array) tools. |
| SPG Session 14 | |
| Room: D | |
| Time: 16:00~18:00, Sunday, September 22, 2019 | |
| Session Chair: Wentao Shi, Northwestern Polytechnical University | |
| Oral Session: | SPG 14-1(Paper ID: 9110) |
| Title: | The application of Kalman filter on source depth discrimination in shallow water |
| Author: | Guangying Zheng, Fangwei Zhu, Chuanxiu Xu, You Shao, Fuchen Liu and Junyu Fu |
| Affiliation: | Science and technology on sonar Laboratory, Hangzhou applied acoustics research institute, Hangzhou, China. |
| Abstract: | Source depth discrimination is very important for underwater anti-submarine warfare. Based on the characteristic of underwater acoustic field excited by shallow source and deep source, this paper illustrates the reason why mode filtering can be used for source depth discrimination and clarifies the discrimination mechanism of trapped mode energy ratio and matched subspace discrimination. Then the performance of two depth discrimination methods is compared with numerical simulation and Swellex-96 vertical array data. While there is significant fluctuation in discrimination characteristic quantity extracted from experimental data, which leads to poor discrimination performance. In order to improve the discrimination performance, Kalman filtering and Kalman smoothing are used to estimate the depth discrimination quantity in this paper. Shallow and deep sources are obviously separable when Kalman filtering and Kalman smoother are used to estimate the depth discrimination quantity from experimental data. |
| Oral Session: | SPG 14-2(Paper ID: 9047) |
| Title: | Research on Optimum Operating Parameters Selection of Active Sonar in Shallow Water |
| Speakers: | Tuo Chen, Qiming Ma and Gongbing Wang |
| Affiliation: | Laboratory, Hangzhou Applied, Acoustics Research Institute, Hangzhou City, Zhejiang Province, China |
| Abstract: | The selection of working parameters of active sonar, especially the selection of working frequency and working depth, has a great influence on the performance of sonar detection. An active sonar detection performance evaluation model is established in this paper based on sonar equation and propagation model. Connecting with the inherent characteristics of the equipment, the transmission loss of different frequencies and depths at different distances is transformed into detection probability, and the performance evaluation objective functions at different frequencies and depths are obtained by integrating detection probability. The optimal operating parameters of active sonar in shallow water under several typical hydrological conditions are simulated and verified by numerical calculation. |
| Oral Session: | SPG 14-3(Paper ID: 9103) |
| Title: | A Maneuvering Multi-target Tracking Algorithm Based on AGMM-CBMeMBer |
| Author: | Linxi Wang, Xiaoxi Hu, Xun Han, Yin Kuang and Xinquan Yang |
| Affiliation: | China Academy of Space Technology, Xi'an, Shaanxi, China. |
| Abstract: | Aiming at the problem that traditional tracking algorithms can not effectively track maneuvering multi-target in clutter environment, this paper proposes a new maneuvering multi-target tracking algorithm based on adaptive grid method and Cardinality Balanced Multi-Target Multi-Bernoulli (CBMEMBer) filtering algorithm. The adaptive adjustment of the model set is realized by introducing the adaptive grid method. Therefore, the proposed algorithm can adapt to the change of the moving state of the maneuvering target. The simulation results show that, compared with the fixed structure multi-model tracking algorithm, the proposed algorithm has better tracking performance for maneuvering multi-target, and its cost-effectiveness ratio is higher. It has a wide application prospect in the field of multi-target tracking. |
| Oral Session: | SPG 14-4(Paper ID: 9215) |
| Title: | On the Underwater Target Detection with Decision Fusion in UASN |
| Author: | Bing Leng, Xiaohong Shen and Yongsheng Yan |
| Affiliation: | School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shaanxi, China. |
| Abstract: | Data fusion in multi-sensor networks can significantly improve the perception gain of targets. We reinvestigated the detection fusion system by considering the local decision rule and fusion rule as a whole. Based on the characteristics of underwater target detection in underwater acoustic sensor network (UASN), we construct a fusion detection system with parallel topology. In such a system, the energy detector is employed in each sensor while the Chair-Varshney and Counting decision fusion strategies are taken into account, respectively. In addition, the decision statistics in each sensor and the fusion statistics in the fusion center are used to determine the detection threshold in each sensor and the fusion center by Monte Carlo simulation. The results show that the performance of fusion system performs much better than single sensor detection system. When the detection distance is larger, Chair-Varshney fusion statistics and Counting fusion statistics have the comparable detection performance. |
| Oral Session: | SPG 14-5(Paper ID: 9202) |
| Title: | Detection Method of Eliminating False Rejection Based on M-Duffing Oscillator with Variable Amplitude Coefficients |
| Author: | Caihong LIU, Qing LI, Zhenjia DOU |
| Affiliation: | Science and Technology on Sonar Laboratory, Hangzhou Applied Acoustics Research Institute, Hangzhou, China. |
| Abstract: | A detection method of Multi-Duffing chaotic oscillator (M-Duffing oscillator) with variable amplitude coefficients is proposed for the problem of Duffing chaotic oscillator system’s miss detection generated by envelope fluctuation and blind angle. The Duffing oscillator detection method has the ability of weak signal detection based on the sensitivity to driving force amplitude. But the envelope fluctuation and blind angle can cause the false rejection detection. Meanwhile, a detection method of M-Duffing chaotic oscillator is adopted here in order to alleviate the influence of phase blind areas and to solve the problem of lacking time-frequency resolution of conventional Duffing oscillator systems. To overcome the shortcomings of the phase diagram discrimination method in quantitative analysis, a Lyapunov exponent identification method is proposed. The results of the experiment verify the feasibility and accuracy of the new approach. |
| SPS Session 01 | |
| Room: A | |
| Time: 10:30~12:30, Sunday, September 22, 2019 | |
| Session Chair: Hongxi Yin, Dalian University of Technology | |
| Session: | Invited Talk 1 |
| Speakers: | Nan Chi. Professor, Key Laboratory for Information Science of Electromagnetic Waves (MoE), Fudan University |
| Title: | Enabling Technologies for High-speed LED Based Underwater Visible Light Communications |
| Abstract: | Underwater optical wireless communication (UWOC) is an emerging area need to be investigated. Nowadays, underwater visible light communication (UVLC) is expected to act as an alternative candidate in next-generation underwater wireless optical communications for the Internet of Underwater Things. The challenge is that the absorption, scattering, diffraction effect and turbulence of water medium, which can bring large attenuation and nonlinearity penalty. Therefore, the advanced modulation formats including carrierless amplitude and phase modulation (CAP), orthogonal frequency division multiplexing (OFDM) and discrete Fourier transform spread orthogonal frequency division multiplexing (DFT-S OFDM) are needed to be applied in UVLC system. What’s more, advanced digital signal processing algorithm such as pre/post equalization, nonlinear compensation and other algorithms based on machine learning are needed. In this paper, we introduce three advanced modulation formats including DFT-S OFDM, OFDM and CAP employing probabilistic shaping for high-speed LED based underwater visible light communication. |
| Session: | Invited Talk 2 |
| Speakers: | Jing Xu. Professor, Ocean College, Zhejiang University |
| Title: | Multi-pixel Photon Counter and Its Application in Underwater Wireless Optical Communications |
| Abstract: | Foreseeing the proliferation of underwater vehicles and sensors, underwater wireless optical communication (UWOC) is a key enabler for ocean exploration, with strong competitiveness in short-range bandwidth-intensive applications. The UWOC transmission distance is severely limited by the rapid decay of light intensity in water. Ultra-sensitive multi-pixel photon counter (MPPC) opens the door toward designing long-reach UWOC systems. |
| Oral Session: | SPS 01-1 (Paper ID: 9038) |
| Title: | Wireless Optical Communication Performance Simulation and Full-duplex Communication Experimental System with Different Seawater Environment |
| Author: | Zhiheng Zhou, Hongxi Yin and Yanxin Yao |
| Affiliation: | Laboratory of Optical Communications and Photonic Technology, School of Information and Communication, Dalian University of Technology, Dalian, Liaoning, China. |
| Abstract: | In this paper, the impacts of transmitter divergence angle, receiver aperture and transmission distance on the performance of underwater wireless optical communication system under different seawater quality conditions are modeled and simulated. A new type of underwater wireless optical communication transmitter module based on OSRAM laser diode is designed and developed. An integrated underwater green optical communication experimental system is built and its performance is tested. A full-duplex Ethernet transmission system with extended distance is established to realize high speed transmission of real-time multi-service over Ethernet. |
| Oral Session: | SPS 01-2 (Paper ID: 9040) |
| Title: | Performance Analysis for Underwater Cooperative Optical Wireless Communications in the Presence of Solar Radiation Noise |
| Author: | Fangyuan Xing and Hongxi Yin |
| Affiliation: | School of Information and Communication, Dalian University of Technology, Dalian, Liaoning, China. |
| Abstract: | Underwater optical wireless communications suffer from several challenges, such as large path loss and limited transmission distance. Cooperative communications are implemented by utilizing relays as virtual antennas to increase diversity gain and expand communication range. In this paper, we investigate the performance of the cooperative transmission for underwater optical wireless communications in the presence of solar radiation noise, which has a detrimental impact on the underwater communications during daytime and in the neritic zone. Firstly, the performance of amplify-and-forward relaying and decode-and-forward relaying based on line-of-sight (LOS) links and non-line-ofsight (NLOS) links is theoretically analyzed. Then, the effects of the horizontal positions and the depths of relays, as well as the allocations of transmitted power on cooperative communications are simulated and evaluated. The main factors affecting the system behavior and the optimal deployment of the relays for LOS and NLOS links are derived through balancing path loss, refraction loss, and solar radiation noise. |
| Oral Session: | SPS 01-3 (Paper ID: 9177) |
| Title: | Modeling and Simulation Analysis of UOWC System in Consideration of Impluse Expansion |
| Author: | Xiuyang Ji, Hongxi Yin, Fangyuan Xing and Zhongwei Shen |
| Affiliation: | School of Information and Communication Engineering, Dalian University of Technology, Dalian, Liaoning, China. |
| Abstract: | The paper attempts to describe the seawater scattering impact on transmitted optical signals, where the mutual correlation of a group of photons in the transmission process is considered. A UOWC system model is established concerning the impulse extension versus the time domain in underwater channels, and the performances under many different circumstances such as transmission distances, bit rates, receiver apertures, transmitted power are simulated and analyzed. |
| Oral Session: | SPS 01-4 (Paper ID: 9032) |
| Title: | Analysis of Received Power in Laser Communication Based on Cat's Eye Modulating Retro-reflector |
| Author: | Shuaijun Duan, Ruifeng Liu, Guihua Fan and Laixian Zhang |
| Affiliation: | Department of Postgraduate, Management, Space Engineering University, Beijing, China. |
| Abstract: | Laser communication based on cat’s eye modulating retro-reflector can achieve a smaller matching size modulator than the other modulating retro-reflector communication modes, thereby achieving a faster communication rate. Considering the attenuation of the laser transmission process and converting the angular misalignment of the cat’s eye lens into a line offset, the large field of view cat-eye retro-reflected modulating echo power model is established based on the Collins diffraction formula. The influence of communication distance, incident angle, defocusing amount, laser wavelength and receiving aperture on received power are simulated. The results show that the received power decreases with the increase of communication distance, laser incident angle and defocusing amount and increases first and then decreases as the laser wavelength increases; the larger the receiving aperture, the greater the receiving power. |
| Oral Session: | SPS 01-5 (Paper ID: 9206) |
| Title: | PAPR Reduction and Multiuser Access Using OFDMA for LiFi |
| Author: | Siyumie Wijesinghe and Rohana Thilakumara |
| Affiliation: | Siyumie Sherin Wijesinghe, Department of Electrical and Computer Engineering, Sri Lanka Institute of Information Technology, Malabe, Sri Lanka. |
| Abstract: | Light Fidelity (LiFi) is a novel optical communication technology used in indoor short range wireless communication, competing Radio Frequency (RF) WiFi technology. This technology increases the transmission capacity in indoor propagation while eliminating unwanted Electromagnetic pollution, multipath interference and security threats in RF technology. While OFDMA in LiFi guarantees a more reliable and flexible communication, the peak to average power ratio (PAPR) could impose practical difficulty in designing LiFi OFDM receivers when more subcarriers are added to form the composite OFDM signal due to the need of a larger dynamic range for the receiver. This work presents a novel PWM (Pulse Width Modulated) OFDM approach for Free Space Optical Communication (FSOC) systems that resolves the PAPR problem while providing multiuser access in the uplink from spatially separated users. The energy of the OFDM signal is translated from vertical to horizontal representation using PWM to reduce PAPR problem. This technique can also removes additive noise in propagation by limiting the signal amplitude at the receiver to increase the robustness to noise. This novel method has the potential for very high data rates in short range wireless optical links while providing multiuser wireless access from spatially separate locations. |
| SPS Session 02 | |
| Room: B | |
| Time: 10:30~12:30, Sunday, September 22, 2019 | |
| Session Chair: Lamei Zhang, Harbin Institute of Technology | |
| Session: | Invited Talk 3 |
| Speakers: | Bin Zou. Professor, School of Electronics and Information, Harbin Institute of Technology (HIT) |
| Title: | Advanced Polarimetric Target Decomposition Techniques |
| Abstract: | Polarimetric synthetic aperture radar (PolSAR) is a well-established technique that allows identification and separation of scattering mechanisms in the polarization signature. PolSAR can identify the fine configuration, orientation and composition of a target using the SAR complex images in different polarimetric channels, and the collection of PolSAR data is less influenced by solar illumination and weather conditions. The PolSAR related researches have been conducted for many years and various methods have been proposed, in which polarimetric target decomposition methods are the predominant ones. Polarimetric target decompositions try to identify and separate the physical scattering mechanisms from the measured PolSAR data by expressing the average mechanism in each resolution cell as the sum of independent elements. The advanced polarimetric target decomposition techniques can effectively represent the scattering characteristics of the target in PolSAR data for purposes of classification and parameter estimation. |
| Oral Session: | SPS 02-1 (Paper ID: 9109) |
| Title: | Change Detection for Mutil-temporal Remote Sensing Images Based on Nsct and Hierarchical Clustering |
| Author: | Qingle Guo and Junping Zhang |
| Affiliation: | 1. School of Electronics and Information Engineering, Harbin, Hei Longjiang, China; 2. Institute of Technology, Harbin, Hei Longjiang, China. |
| Abstract: | Change detection for remote sensing image is of great significance to a diverse range of applications, such as urban development, environment and damage monitoring. Some typical methods are difficult to maintain detail information and the detection accuracy is also not satisfied. In this paper, a detail-injecting approach based on nonsubsampled contourlet transform (NSCT) and hierarchical clustering is presented to preserve the detail information and increase the separability of the intermediate classes to improve the accuracy. The strategy of detail-injecting based on NSCT is to extract the detail information, and then inject the detail to difference image. After that, the residual image which have been highlighted by histogram contrast (HC) model is used as input of the strategy of hierarchical clustering to obtain the final result. The experiments show that, comparing with some typical methods, the method proposed in this paper has a superior performance in change detection for remote sensing image. |
| Oral Session: | SPS 02-2 (Paper ID: 9172) |
| Title: | Real-time Detection of Facial Expression Based on Improved Residual Convolutional Neural Network |
| Author: | Sen Wang, Xiaofei Wang, Runxing Chen, Yong Liu and Shuo Huang |
| Affiliation: | Electronic Engineering College, Heilongjiang University, Hei Longjiang, China. |
| Abstract: | An improved residual convolutional neural network is designed for real-time expression detection algorithms. The depth-wise separable convolutional layer is used instead of the standard convolutional layer, and the global average pooling is used instead of the fully connected layer. And the residual block is used to solve the phenomenon that the overfitting and the gradient disappear due to the excessive number of layers when the number of network layers is increased. This paper uses the FER-2013 face dataset to train the network model. Compared with the standard convolutional neural network, the parameters in the network are greatly reduced and the size of the model is reduced. Experiments show that the rate of facial expression recognition proposed in this paper is greatly improved. |
| Oral Session: | SPS 02-3 (Paper ID: 9174) |
| Title: | Hyperspectral Image Classification Based on Bidirectional Recurrent Neural Network |
| Author: | Shuo Huang, Xiaofei Wang, Hongchang He, Yong Liu and Runxing Chen |
| Affiliation: | Electronic Engineering College, Heilongjiang University, Hei Longjiang, China. |
| Abstract: | In recent years, the rise of machine learning algorithms provides a good tool for processing hyperspectral data. A series of machine learning algorithms have served for the classification of hyperspectral images. Derived from these methods that regarding spectral segments of each pixel as a spectral sequence. Recurrent Neural Network (RNN) showing better processing capability for sequence data play an important role in hyperspectral data classification. The standard unidirectional RNN, however, only focus on the current input and the memory state of the past, and cannot connect to the future memory. Alternatively, in this paper, bidirectional RNN(BiRNN) is employed for the classification of hyperspectral images for the future memory. BiRNN can integrate the past memory and future memory state. The proposed method is applied to a classical hyperspectral data set, the performance of classification is better. |
| Oral Session: | SPS 02-4 (Paper ID: 9194) |
| Title: | The Comparison of deep learning recognition methods based on SAR image |
| Author: | ZHAI Jia1，ZHU Sha2 and CHEN Feng1 |
| Affiliation: | 1. Science and Technology on Electromagnetic Scattering Laboratory，Beijing, China; 2. Beijing Institute of Remote Sensing Information，Beijing, China. |
| Abstract: | To solve existing problems of synthetic aperture radar (SAR) target recognition, some new methods of deep learning recognition are proposed. The stacked autoencoder (SAE) network and the convolutional neural network (CNN) perform noticeably well. In this paper, the realization and the comparison of these methods will show that the proposed method of deep learning recognition is adaptive to different occasion and both robust to the attitude angle, background and noise. |
| Oral Session: | SPS 02-5 (Paper ID: 9197) |
| Title: | Satellite-borne SAR low-contrast signals wave wake image enhancement based on a bilateral rapid filtering visualization algorithm |
| Author: | Sha Zhu, Zhuo Chen and Lihong Kang |
| Affiliation: | Beijing Institute of Remote Sensing Information Beijing, China |
| Abstract: | Aiming at solving the problem of satellite-borne SAR low-contrast signal processing, in order to improve the radiation resolution of SAR images, a visualized enhancement algorithm based on bilateral rapid filtering algorithm was proposed. The accuracy of the proposed methods has been demonstrated by the results based on real data. The radiation resolution of SAR images has been improved, which will benefit for sea surface target detection and classification. |
| SPS Session 03 | |
| Room: A | |
| Time: 13:30~15:30, Sunday, September 22, 2019 | |
| Session Chair: Jie Chen, Northwestern Polytechnical University, Wei Gao, Jiangsu University, | |
| Session: | Invited Talk 4 |
| Speakers: | Qing Ling. Professor, School of Data and Computer Science, Sun Yat-sen University |
| Title: | RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets |
| Abstract: | We propose a class of robust stochastic subgradient methods for distributed learning from heterogeneous datasets at presence of an unknown number of Byzantine workers. The Byzantine workers, during the learning process, may send arbitrary incorrect messages to the master due to data corruptions, communication failures or malicious attacks, and consequently bias the learned model. The key to the proposed methods is a regularization term incorporated with the objective function so as to robustify the learning task and mitigate the negative effects of Byzantine attacks. The resultant subgradient-based algorithms are termed Byzantine-Robust Stochastic Aggregation methods, justifying our acronym RSA used henceforth. In contrast to most of the existing algorithms, RSA does not rely on the assumption that the data are independent and identically distributed (i.i.d.) on the workers, and hence fits for a wider class of applications. Theoretically, we show that: i) RSA converges to a near-optimal solution with the learning error dependent on the number of Byzantine workers; ii) the convergence rate of RSA under Byzantine attacks is the same as that of the stochastic gradient descent method, which is free of Byzantine attacks. Numerically, experiments on real dataset corroborate the competitive performance of RSA and a complexity reduction compared to the state-of-the-art alternatives. |
| Oral Session: | SPS 03-1 (Paper ID: 9027) |
| Title: | Diffusion Approximated Kernel Least Mean P-Power Algorithm |
| Author: | Wei Gao1, Jie Chen2 and Lingling Zhang2 |
| Affiliation: | 1. School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu, China; 2. School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shanxi, China. |
| Abstract: | Considering nonlinear and non-Gaussian environments that are frequently encountered in practice, in this paper we propose the approximated kernel least mean p-power (AKLMP) algorithm for addressing these factors in the distributed systems. In order to efficiently devise this algorithm, we propose to approximate the shift-invariant kernel by random Fourier features, and to consider the impulsive noise modeled by theα-stable distribution. The stability in the mean of proposed distributed algorithm is then studied. Finally, the superiority of proposed approach compared to diffusion kernel least-mean-square (KLMS) algorithm is confirmed by experimental results. |
| Oral Session: | SPS 03-2 (Paper ID: 9044) |
| Title: | Distributed Estimation for Sparse Parameter Based on Fused-lasso Technique |
| Author: | Wei Huang, Chao Chen, Xinwei Yao and Qiang Li |
| Affiliation: | College of Computer Science, Zhejiang University of Technology, Hangzhou, Zhejiang, China. |
| Abstract: | Estimation for sparse parameter in adaptive networks has become a hot topic recently in the field of adaptive filtering. In some cases, the sparsity feature may also be found in the differences of successive entries of the true parameter, i.e. the non-zero elements may be assembled in one or more regions of the true parameter. In this paper, we propose the fused sparse diffusion LMS algorithm for recovering such parameter. The proposed algorithm relies on sparse regularization term to enforce sparsity of entries themselves, and fused sparse regularization term to enforce similarity of adjacent non-zero entries. We then provide the conditions for the convergence of the proposed algorithm in the mean sense. Numerical simulations are conducted to show the superiority of our proposed algorithm over several other algorithms. |
| Oral Session: | SPS 03-3 (Paper ID: 9069) |
| Title: | Randomized ULV Decomposition for Approximating Low-Rank Matrices |
| Author: | Maboud Kaloorazi and Jie Chen |
| Affiliation: | School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shanxi, China. |
| Abstract: | In this paper, we present a low-rank matrix approximation algorithm called Randomized Rank-k ULV (RR-ULV) decomposition. Fundamental in our work is the exploitation of the randomized sampling paradigm, which provides an efficient strategy in order to construct an approximation of a large input matrix. Our proposed RR-ULV is computationally efficient, robust, highly accurate, and also can take advantage of modern computational platforms. We apply RR-ULV to synthetic data and real world data of image reconstruction as well as robust principal component analysis problems to show its efficacy and efficiency. Our experimental results show that RR-ULV outperforms the existing methods. |
| Oral Session: | SPS 03-4 (Paper ID: 9212) |
| Title: | Robust nonnegative mixed-norm algorithm with weighted l1-norm regularization |
| Author: | Yifan Wu and Jingen Ni |
| Affiliation: | School of Electronic and Information Engineering, Soochow university, Suzhou, China. |
| Abstract: | Nonnegativity as a constraint has attracted much attention in recent years. The recently proposed sign-sign nonnegative least mean square (NNLMS) algorithm is robust against impulsive noise but suffers from slow convergence rate. This paper proposes a nonnegative mixed-norm algorithm with faster convergence rate than sign-sign NNLMS. To further improve the convergence rate of indentifying sparse systems with nonnegativity constrains, we apply the weighted l1-norm of the adaptive filter weight vector as a regularization term to the cost function of the estimation error. Simulation results are provided to illustrate the superior performance. |
| SPS Session 04 | |
| Room: B | |
| Time: 13:30~15:30, Sunday, September 22, 2019 | |
| Session Chair: Fengzhong Qu, Zhejiang University, Qunfei Zhang, Northwestern Polytechnical University | |
| Session: | Invited Talk 5 |
| Speakers: | Jun Tao. Professor, School of Information Science and Engineering, Southeast University |
| Title: | A Fast Proportionate RLS Adaptive Equalization for Underwater Acoustic Communications |
| Abstract: | A low-complexity recursive least squares (RLS) type sparse direct adaptive equalizer (DAE) is proposed for multiple-input multiple-output (MIMO) underwater acoustic (UWA) communications. The underlying proportionate RLS (PRLS) adaptive filter algorithm is motivated by the idea of proportionate updating (PU) originated in the improved proportionate normalized least mean squares (IPNLMS) adaptive filter scheme. To overcome the high complexity of the PRLS that is quadratic in the filter size, a fast implementation is developed in a way similar to the design of the stable fast transversal filter (SFTF) as a low-complexity approximation of the standard RLS adaptive filter algorithm. The resulting fast version of the PRLS is named the proportionate SFTF (PSFTF). The PSFTF is then adopted to update coefficients of a linear equalizer (LE), which was tested by experimental data collected in at-sea UWA communication trials. Experimental results showed the PSFTF-DAE achieves faster convergence and better performance than existing SFTF-DAE and RLS-DAE. |
| Oral Session: | SPS 04-1 (Paper ID: 9125) |
| Title: | Chaotic Composite Spread Spectrum Sequence Based PAPR Suppression for Underwater Acoustic MC-CDMA Communication System |
| Author: | Lanjun Liu, Hui Ren, Peng Zhai, Jiong Niu, Hao Zhao and Jicun Mao |
| Affiliation: | College of Engineering, Ocean University of China, Qingdao, Shandong, China. |
| Abstract: | As a combination of orthogonal frequency division multiplexing (OFDM) and code division multiple access (CDMA) modulation technology, underwater acoustic multi carrier code division multiple access (MC-CDMA) communication system also has the problem of high peak-to-average power ratio (PAPR). In this paper, a method of PAPR suppression for underwater acoustic MC-CDMA communication system based on chaotic composite spread spectrum sequence is proposed. Chaotic composite spread spectrum sequence is generated by combining chaotic sequence and spread spectrum sequence. First, chaotic sequence is generated according to the number of subcarriers. Then chaotic composite spread spectrum sequence is generated by cyclic multiplication of chaotic sequence and spread spectrum sequence. Spread spectrum sequence adopts M sequence, Walsh sequence and complete complementary sequence, respectively. The simulation results show that the chaotic composite spread spectrum sequence has better PAPR suppression ability in different degrees than the original spread spectrum sequence. In the case of 32 chips, chaotic composite spread spectrum sequence achieves 5 ~ 6 dB PAPR suppression performance gain. |
| Oral Session: | SPS 04-2 (Paper ID: 9153) |
| Title: | A High Spectral Efficiency Marine Mammal-Friendly Routing Protocol for Underwater Acoustic Networks |
| Author: | Xinrui Zhang1,2, Yougan Chen1,2, Jianying Zhu1,2, Weijian Yu1,2, Xiaokang Zhang1,2 and Xiaomei Xu1,2 |
| Affiliation: | 1.Xiamen University, Xiamen, Fujian, China; 2. Shenzhen Research Institute of Xiamen University, Shenzhen, China. |
| Abstract: | In general, all the sensor nodes, marine mammals and other artificial acoustic networks share scarce spectrum resource in the underwater acoustic networks (UANs). To improve the utilization of spectrum resource, this paper proposes a high spectral efficiency marine mammals-friendly routing (HE-MFR) protocol for UANs, which making full use of the interlacing zone of frequency bands that marine mammals relied on and UANs operated on. According to various sound signal types produced by marine mammals, the proposed protocol adopts detour forwarding paths to transmit packets at certain times in order to avoid the interference between the sensor nodes and the mammals, and to shorten the distance of path at the same time. Simulation results show that the proposed protocol has significant advantage in energy consumption compared with the traditional bio-friendly cognitive underwater acoustic network routing (BF-CAR) protocol. |
| Oral Session: | SPS 04-3 (Paper ID: 9223) |
| Title: | Array Manifold Error Correction Using Information of Opportunity Sources in Shallow Sea |
| Author: | Yong Chen and Fang Wang |
| Affiliation: | College of Physics and Communication Electronics, Jiangxi Normal University, Nanchang, Jiangxi, China. |
| Abstract: | Array manifold error makes the performance of adaptive beamforming methods and direction estimation methods seriously degraded. In this paper, an array manifold error correction method based on opportunity source information is proposed. First, there are many opportunity sources in the shallow sea such that the direction information of the opportunity source near the hydrophone array can be easily obtained. Second, using the eigen-decomposition of the signal covariance matrix and the precise direction information of the opportunity source, the array manifold error is corrected by the subspace method. Computer simulation results show that the performance of adaptive beamforming methods and direction estimation methods is significantly improved due to the accurate correction of array manifold errors. |
| Oral Session: | SPS 04-4 (Paper ID: 9053) |
| Title: | Signal Detection for Full-duplex Cognitive Underwater Acoustic Communications with SIC Using Model-Driven Deep Learning Network |
| Author: | Junfeng Wang1, Yue Cui2, Haixin Sun3, Mingzhang Zhou3, Biao Wang4, Jianghui Li5, Lanjun Liu6 and Shexiang Ma1 |
| Affiliation: | 1. School of Electrical and Electronic Engineering, Tianjin University of Technology, Tianjin, China; 2. College of Computer and Information Engineering, Tianjin Normal University, Tianjin, China; 3.School of Information Science and Engineering, Xiamen University, Xiamen, China; 4. College of Electronic and Information Engineering, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu, China; 5. Institute of Sound and Vibration Research, University of Southampton, Southampton, SO17 1BJ UK; 6. College of Engineering, Ocean University of China, Qingdao, China. |
| Abstract: | This paper aims to handle the model-driven deep learning network based signal detection for full-duplex cognitive underwater acoustic communications (FDCUACs) with self-interference cancellation (SIC). The FDCUACs play an important role in underwater wireless communications, which employs the index modulation-orthogonal frequency division multiplexing-spread spectrum (IM-OFDM-SS) that carries subcarrier index bits and symbol bits simultaneously to further enhance data rate. It is shown that the proposed signal detector for the FDCUACs with the SIC can be modelled as a model-driven deep learning network, i.e., an easy index bit recovering processor utilizing the uniqueness behavior of spread codes plus a deep learning network with eight essential layers employed to directly regain the data belonging to the pre-selected carrier index in the transmitter. Compared with the original receiver and signal detection for the IM-OFDM-SS communications, the proposed scheme omits the traditional steps such as channel estimation, equalization and demodulation, and demonstrates the remarkable performance. |
| Oral Session: | SPS 04-5 (Paper ID: 9070) |
| Title: | Proportionate Minimum-Symbol-Error-Rate Based Sparse Equalization for Underwater Acoustic Channels |
| Author: | Wu Ailing1, Wang Zhenzhong2, Chen Fangjiong1, Yu Hua1 and Ji Fei1 |
| Affiliation: | 1. School of Electronics and Information Engineering, South China University of Technology, Guangzhou, Guangdong, China; 2. Guangdong Electric Power Communication Technology Co., Ltd., Guangzhou, Guangdong, China. |
| Abstract: | The minimum-symbol-error-rate (MSER) decision feedback equalizer (DFE) has been developed for underwater channels. Comparing with conventional normalized least-mean square (NLMS) with DFE, MSER-DFE shows significant performance improvement in terms of bit-error-rate (BER). However, it suffers from slow convergence. In this paper, to improve the convergence speed of MSER-DFE, we modify the objective function to exploit the sparsity of the channel equalizer and use the sparseness measure, which is referred to as sparse control proportionate minimum-symbol-error-rate (SC-PMSER) DFE. By assigning larger weights to equalizer taps with larger values, we can speed up the convergence of the proposed equalizer at the cost of higher computational complexity. Simulation results show the effective of the proposed detector. |
| BSPC Session 01 | |
| Room: D | |
| Time: 08:30~10:15, Sunday, September 22, 2019 | |
| Session Chair: Jing Han, Northwestern Polytechnical University | |
| Oral Session: | BSPC 01-1 (Paper ID: 9014) |
| Title: | Doppler Estimation Based on HFM Signal for Underwater Acoustic Time-varying Multipath Channel |
| Author: | Shiduo Zhao, Shefeng Yan and Lijun Xu |
| Affiliation: | Institute of Acoustics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China. |
| Abstract: | The underwater acoustic (UWA) channel is time-varying and suffers from severe multipath delay spread, which causes great difficulties for Doppler estimation. The existing Doppler estimation methods either perform poorly in multipath environment or have to assume that the channel parameters remain unchanged within a relatively long time, which makes their performances unsatisfactory in practical applications. In this paper, we proposed a novel preamble-based Doppler estimation method. This method uses two hyperbolic frequency modulation (HFM) signals with different frequency sweeping directions as the preamble, and exploits the structure of the matched filter outputs of the two HFM signals at the receiver to obtain the Doppler estimation. At the cost of slightly increased computational complexity, this method can match the time-varying multipath channel automatically and achieve an accurate and robust Doppler estimation in time-varying multipath UWA channel under the reasonable assumption that the channel is fixed only within the duration of the preamble. Both simulation results and the experimental results in Thousand Island Lake show great promise of this approach. |
| Oral Session: | BSPC 01-2(Paper ID: 9033) |
| Title: | Off-grid Direction of Arrival Estimation Based on Acoustic Vector Sensor Array |
| Author: | Weidong Wang1, Qunfei Zhang1, Wentao Shi1, Weijie Tan1, Xuhu Wang2 |
| Affiliation: | 1. School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, China; 2. School of Communication and Electronic Engineering, Qingdao University of Technology, Qingdao, China. |
| Abstract: | The off-grid phenomenon affects the accuracy of the direction of arrival (DOA) estimation when implementing the sparsity-based method for classical long vector acoustic vector sensor (LVAVS) array. To address this problem, an iterative alternating off-grid algorithm for LVAVS array is proposed. This algorithm formulates the off-grid model by introducing a bias parameter into the signal model of LVAVS array, and recoveries the joint sparsity signal and calculates the unknown bias parameter by iterative alternating way. Simulation experiments show that compared with the state-of-the-art algorithms, the proposed algorithm improves the DOA estimation accuracy in the presence of a coarse sample gird and has less computational cost. |
| Oral Session: | BSPC 01-3 (Paper ID: 9054) |
| Title: | Transmit Beampattern Design Method for MIMO Radar Based on Prior Information |
| Author: | Junsheng Huang, Hongtao Su and Bin He |
| Affiliation: | National Laboratory of Radar Signal Processing, Xidian University, Xi'an, China. |
| Abstract: | In this paper, a transmit beampattern design method for multiple input multiple output (MIMO) radar based on prior information is proposed, so as to efficiently suppress the sidelobe non-homogeneous clutter. Firstly, the average power of clutter-plus-noise signal in the received echoes is estimated by transmitting a known waveform. Then, the transmit waveform covariance matrix is optimized by constructing the optimization model of maximizing the signal-to-clutter-plus-noise ratio of the received echoes, which can be effectively solved by using the semidefinite programming method. Finally, the obtained transmit waveform covariance matrix is utilized to synthesis the transmit beampattern. Simulation results demonstrate the validity of the proposed method. |
| Oral Session: | BSPC 01-4 (Paper ID: 9065) |
| Title: | Anisotropic Instantaneous Frequency Estimator |
| Author: | Yongchun Miao1, Haixin Sun1 and Junfeng Wang2 |
| Affiliation: | School of Information Science and Engineering, Xiamen University, Xiamen, China; 2. School of Electrical and Electronic Engineering, Tianjin University of Technology, Tianjin, China. |
| Abstract: | We present a novel transform, called anisotropic chirplet transform, for the time-frequency analysis of overlapping signals. This transform is motivated by a desire to characterize micro-Doppler signals from the continuous wave radars, especially a challenging topic for instantaneous frequency (IF) estimation in high noise environments. By combining the instantaneous rotating angle with the anisotropic operator, anoptimal time-frequency-varying window width is achieved to directionally compensate for the energy of each component. In addition, the chirplet ridge detection algorithm based on the anisotropic chirplet transform is further proposed to extract chirplet ridges in noisy signals. The proposed method is applied to analyze overlapping multicomponent signals with a high noise, which demonstrates its effectiveness in the simulated examples and application data sets. |
| Oral Session: | BSPC 01-5 (Paper ID: 9079) |
| Title: | Atomic Norm Minimization Methods for Continuous DOA Estimation in Colored Noise |
| Author: | Yuying Zhang1, Gong Zhang1 and Leung Henry2 |
| Affiliation: | 1. Nanjing University of Aeronautics and Astronautics, Nanjing, China; 2. Department of Electrical and Computer Engineering, University of Calgary, Calgary, Canada. |
| Abstract: | This paper aims to deal with the problem of continuous direction-of-arrival (DOA) estimation, and is focused on developing grid-less sparse methods to colored noise environment. We propose a two-stage grid-less model based on noise suppression and sparse representation. Then the simplified two-dimensional atomic norm minimization algorithm is proposed to estimate parameters. We further extend a reduced-complexity algorithm to the reconstruction of difference covariance matrix. The unknown DOAs are retrieved |
| BSPC Session 02 | |
| Room: D | |
| Time: 10:30~12:30, Sunday, September 22, 2019 | |
| Session Chair: Peter Tam, Hong Kong Polytechnic University | |
| Oral Session: | BSPC 02-1 (Paper ID: 9101) |
| Title: | RF Vector-Multiplier Compensation for Self-Interference Cancellation in Full-Duplex Radios |
| Author: | Seong Kyu Leem and Sung Ho Cho |
| Affiliation: | Department of Electronics and Computer Engineering, Hanyang University, Seoul, South Korea. |
| Abstract: | Full-duplex radios have been receiving considerable attention due to their ability to simultaneously transmit and receive signals. However, the main challenge in full-duplex radio is the elimination of the self-interference (SI) signal, which is a transmission signal that leaks to the receiver. In this paper, we investigate the effect of the imperfection of the radio frequency vector multiplier (RF-VM) used for removing the SI signal in a full-duplex radio on the SI cancellation performance, and propose a compensation method. The RF-VM has mismatch between the inphase and quadrature paths of the internal hybrid coupler, and imperfections, such as gain and phase mismatch, between the baseband control lines. We derive the equation for the received signal after SI removal using the channel responses of the SI and cancellation paths, and the filter response for RF-VM impairment modeling in a full-duplex radio transceiver. Based on this, we propose a method for obtaining the RF-VM baseband control signal, which compensates the RF-VM impairment and maximizes the SI cancellation performance. The proposed scheme is verified by simulation, through which the effect of RF-VM impairment on the SI cancellation performance is investigated and confirmed to be effectively compensated by the proposed method. |
| Oral Session: | BSPC 02-2 (Paper ID: 9116) |
| Title: | Joint Doppler Scale Estimation and Timing Synchronization in Underwater Acoustic Communications |
| Author: | Zhiqiang Ling1, Lei Xie11,2 and Huifang Chen1,3 |
| Affiliation: | 1. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, Zhejiang, China; 2. Zhejiang Provincial Key Laboratory of Information Processing, Communication and Networking, Hangzhou, China; 3. Zhoushan Ocean Research Center, Zhoushan, Zhejiang, China. |
| Abstract: | In underwater acoustic communication systems, Doppler effect caused by the relative motion of transmitter and receiver will seriously deteriorate the performance. In this paper, we propose a joint Doppler scale estimation and timing synchronization method in underwater acoustic communications, where the superimposed hyperbolic frequency modulation (HFM) signal is used as the preamble. The timing position and the Doppler factor are simultaneously obtained by two parallel correlators of the received signals. Simulation results show that the proposed method can estimate the Doppler factor correctly, as well as correcting the deviation of timing synchronization. Compared with the traditional method, the proposed joint Doppler scale estimation and timing synchronization method achieves a better performance. In addition, the results of a sea experiment demonstrate the feasibility of the proposed method. |
| Oral Session: | BSPC 02-3 (Paper ID: 9122) |
| Title: | A Cost-effective Method for Epileptic Seizure Classification |
| Author: | Md Mursalin1, Syed Mohammed Shamsul Islam1 and Adel Al-Jumaily2 |
| Affiliation: | 1.Edith Cowan University, Perth, Australia; 2. University of Technology Sydney, Sydney, Australia. |
| Abstract: | The ongoing development of various lightweight and portable EEG signal acquisition devices provides the opportunity to implement home-based epilepsy monitoring. However, it is essential to apply a highly effective method to handle the limited computational power of such devices. In this paper, we propose a cost-effective method to classify epileptic seizure using stratified sampling technique. Additionally, to reduce the required computational power, this paper proposes a novel correlation and threshold-based feature selection algorithm. For evaluating the performance of our proposed method, five different classification algorithms are applied to classify the epileptic seizure from the reduced feature set. In our experiment, the random forest classifier shows the highest accuracy compared to other classifiers. |
| Oral Session: | BSPC 02-4 (Paper ID: 9127) |
| Title: | Low Complexity Short Baseline Localization Algorithm Based on Taylor Expansion |
| Author: | Xiaoyan You1,2, Yanbo Wu2,3,4, Min Zhu2,3,4, Xinguo Li2,4 and Linyuan Zhang2,4 |
| Affiliation: | 1. University of Chinese Academy of Sciences, Beijing, China; 2. Ocean Acoustic Technology Center, Institute of Acoustics, Chinese Academy of Sciences, Beijing, China; 3. State Key Laboratory of Acoustics, Chinese Academy of Sciences, Beijing, China; 4.Beijing Engineering Technology Research Center of Ocean Acoustic Equipment, Beijing, China. |
| Abstract: | Traditional short baseline positioning algorithm suffers from low positioning accuracy and exhaustive search algorithm has high complexity. This paper addresses the problem by introducing a low complexity underwater acoustic short baseline positioning algorithm. First, the positioning principle of short baseline system is studied. After that ingredients that affect estimate accuracy are analyzed, and then the modified algorithm is proposed: based on the exhaustive idea, the performance evaluation function is established first; then it is simplified by Taylor expansion formula; finally, the estimated position is achieved by minimizing it. In the proposed algorithm, linear operations such as multiplication and addition are used instead of square root calculation, thus it can reduce the computational complexity. Furthermore, fixed-point calculation can be realized using the ranging information between the underwater autonomous vehicle (AUV) and the beacon. Simulation results show the effectiveness of the proposed algorithm. |
| Oral Session: | BSPC 02-5 (Paper ID: 9208) |
| Title: | Estimation of Underwater Acoustic Channel via Block-Sparse Recursive Least-Squares Algorithm |
| Author: | Tian Tian, Feiyun Wu and Kunde Yang |
| Affiliation: | School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shaanxi, China |
| Abstract: | Underwater acoustic communication suffers from the serious multipath effect and fast time variation due to the sophisticated ocean environment. General channel estimation schemes have limited performance in underwater acoustic communication because of the lacking exploitation of the underwater acoustic channel (UAC) inherent property. In this work, we address a new approximate mixed ℓ2,0-norm, and based on that norm, we develop a block-sparse recursive least-squares (BS-RLS) algorithm for UAC estimation which takes advantage of the underlying block-sparse structure of UAC. The simulation result shows that the proposed BS-RLS algorithm improves the channel estimation quality under block-sparse condition. |
| COM Session 01 | |
| Room: C | |
| Time: 13:30~15:30, Saturday, September 21, 2019 | |
| Session Chair: Chengkai Tang, Northwestern Polytechnical University | |
| Oral Session: | COM 01-1 (Paper ID: 9050) |
| Title: | Research on Hierarchical Division of Topology in Communication Network |
| Author: | Hongyu Liu1,2 and Mangui Liang1,2 |
| Affiliation: | 1. Institute of Information Science, Beijing Jiaotong University, Beijing, China; 2. Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China. |
| Abstract: | The routing of large-scale communication network is a NP problem. There is a consensus in the industry that hierarchical division of network can solve this problem and ensure the scalability of the network system. Vector Network (VN), as a new network architecture, requires the network to meet the requirements of QoS, reliability and security under scalable condition. This paper studies the division method of multi-level communication network, which is the basic technology for the excellent performance of vector network. Based on the Louvain community division algorithm, this paper proposes an improved Louvain algorithm. This algorithm can effectively divide the network into hierarchical structure. And the experimental results show that the new algorithm improves the execution efficiency and achieves good results. |
| Oral Session: | COM 01-2 (Paper ID: 9073) |
| Title: | ComBot for Inspection and Fault Monitoring/Reporting of Telecommunication Mast Elements |
| Author: | Dinithi Karunasena, Udaya Dampage, Ruvin Kularathna, Oshika Senarathna and Kasun Madhuwantha |
| Affiliation: | Department of Electrical, Electronic & Telecommunication Engineering, General Sir John Kotelawala Defence University Rathmalana, Sri Lanka. |
| Abstract: | Inspection and maintenance activities of the communication masts associated with numerous hazards and risks such as fall dangers, risks related to structural collapses, inappropriate rigging, raising practices, ‘struck-by’ dangers etc. Also a risk for exposure to sudden RF radiation is another essential factor that is needed to consider regarding the periodic maintenance inspections. The utmost thing is the safety of the riggers and those who are performing relevant inspections. Therefore this project endeavors to design a robotic climber for inspection and online/offline monitoring/reporting of communication mast elements. This study explores the development of a mobile climbing robot which can perform corrosion detection testing inspections using a hall effect sensor and which can do the online/offline monitoring/reporting of communication mast elements. This mobile robot walks on the bracings of the communication masts. The movement is based on the leech mechanism with four arms of 2 DoF equipped with eight servo-motors and four electro-magnets. Results of the extensive tests shows that the model can be applied to execute the monitoring and inspection assignments controlled by the operator. |
| Oral Session: | COM 01-3 (Paper ID: 9222) |
| Title: | Implementation of High Frequency Electronic Circuit Experimental Teaching Reform |
| Author: | Chengkai Tang, Tao Bao, Huajie Lin and Yi Zhang |
| Affiliation: | School of Electronics and Information, Northwestern Polytechnical University, Xi’an, Shanxi, China. |
| Abstract: | High frequency electronic circuit is a compulsory course for electronic information majors in Colleges and universities. It plays an important basic role in training students in electronic technology. The original experiment teaching of high frequency electronic circuit is hard to meet the needs of the society for electronic talents through the basic circuit to realize the experiment teaching. This paper presents a reform method of experimental teaching of high frequency electronic circuits. The experiment teaching of high frequency electronic circuit system at the system level is realized through four steps: experiment cognition, experiment design, teacher guidance and experiment evaluation. In order to cope with the future development and change and cultivate new electronic talents with international competitiveness, we should reform the curriculum content from the perspective of depositing the theoretical basis of discipline, focus on training practical ability of students, and emphasize the cultivation of students' subject thinking intuition and professional technical literacy. |
| Oral Session: | COM 01-4 (Paper ID: 9224) |
| Title: | Target Detection Algorithm with Information Geometry under Cooperative Position |
| Author: | Jun Liu1,2, Yi Zhang1, Chengkai Tang1 and Jiaqi Liu1 |
| Affiliation: | 1. School of Electronics and Information, Northwestern Polytechnical University, Xi’an, Shaanxi, China; 2. Shaanxi Key Laboratory of Integrated and Intelligent Navigation, Xi’an, Shaanxi, China. |
| Abstract: | Due to the display of the advantages and advantages of "stealth" weapons and equipment in modern warfare, the trend of invisibility and miniaturization of new weapons and equipment is becoming more and more obvious. Therefore, exploring and researching the detection methods for these weapons and equipments has a strong military application value. Based on electromagnetic field theory and information geometry theory, this paper obtains electromagnetic wave excitation potential in electromagnetic space, and then acquires multi-point electromagnetic wave state potential changes through passive receivers in space, and constructs Riemann geometric statistics by using electromagnetic space situation big data. Manifolds, perceptions and discoveries may enter targets in the electromagnetic space region and their positional orientation. Finally, the electromagnetic potential data of the cyberspace is used to quickly find and identify the target, and the rapid discovery and effective identification of the low, slow, low and fast targets are realized. Finally, the performance of the algorithm is analyzed by experimental simulation from the aspects of target scattering intensity, time base and position reference. |
| Oral Session: | COM 01-5(Paper ID: 9226) |
| Title: | INS Aided High Dynamic Single Satellite Position Algorithm |
| Author: | Jiaqi Liu1,2, Yi Zhang1, Chengkai Tang1 and Xingxing Zhu1 |
| Affiliation: | 1. School of Electronics and Information, Northwestern Polytechnical University, Xi’an, Shaanxi, China; 2. Shaanxi Key Laboratory of Integrated and Intelligent Navigation, Xi’an, Shaanxi, China |
| Abstract: | Because the Global Navigation Satellite System (GNSS) is easily disturbed and easily destroyed, the single-satellite positioning system can be rapidly deployed and provide a long-term space-based passive positioning service under the condition of GNSS rejection. In order to improve the dynamic positioning accuracy of single-satellite navigation in emergency situations, this paper proposes an inertial navigation system (INS)-assisted dynamic single-satellite positioning algorithm. The algorithm combines the dynamic target acceleration measured by the INS and the pseudo-range between the satellite and the target. Using the unscented Kalman filter (UKF) for fusion filtering to solve the position information of the target, which can effectively improve the positioning accuracy of the single-satellite system for the dynamic target. Under the same comprehensive error simulation condition, compared with the single-satellite positioning systems using least squares iteration method and extended Kalman filter (EKF), the positioning error of the algorithm is reduced by 99% and 80% respectively. Effective space-based location service can be provided for dynamic targets in the condition of GNSS system rejection. |
| Oral Session: | COM 01-6 (Paper ID: 9099) |
| Title: | Research on Mobile Spread Spectrum Underwater Acoustic Communication |
| Author: | Pengyu Du, Shengjun Xiong and Chao Wang |
| Affiliation: | Science and Technology on Sonar Laboratory, Hangzhou Applied Acoustic Research Institute, Hangzhou, Zhejiang, China. |
| Abstract: | Direct-sequence spread-spectrum (DSSS) underwater acoustic (UWA) communication can obtain considerable matching processing gain at the receiving end, which is the preferred communication method for high quality underwater acoustic communication. However, under the mobile condition, the DSSS receiving signal will face fast carrier phase fluctuation interference, resulting in a serious degradation of the matching processing gain at the receiving end. Aiming at this problem, this paper proposes a dual differential spread-spectrum (DDSS) UWA communication technology: double differential encoding of the original information sequence at the transmitting end; dual-difference correlation detector for decoding at the receiving end, which can effectively suppress fast carrier phase interference. The simulation results show that the DDSS UWA communication can achieve -8dB SNR robust acoustic communication under the condition of relative motion speed of 8m/s, and the communication error rate is less than 10-3. |
| COM Session 02 | |
| Room: C | |
| Time: 16:00~18:00, Saturday, September 21, 2019 | |
| Session Chair: Linlin Mao, Institute of Acoustics, Chinese Academy of Sciences | |
| Oral Session: | COM 02-1 (Paper ID: 9028) |
| Title: | Implementation of Space-time Coding and Decoding Algorithms for MIMO Communication System Based on DSP and FPGA |
| Author: | Weiping Tang, Shouguo Yang, Xingcheng Li |
| Affiliation: | Air and Missile Defense College, Air Force Engineering University, Xi'an, Shaanxi, China. |
| Abstract: | Multiple input multiple output (MIMO) communication technology will be widely used in future mobile communication system. And the space-time coding and decoding algorithms are key algorithms in MIMO communication technology. In this paper the space-time coding and decoding principle and algorithms of Alamouti scheme are analyzed. To verify the algorithms the MIMO communication experimental platform is designed. The baseband part of the platform is based on DSP and FPGA architecture. FPGA is mainly used to realize bus interface between modules. And DSP is used to accomplish the space-time coding and decoding algorithms and execute the data exchange scheduling strategy. All these ensure the effective implementation of the algorithms and efficient scheduling of data. The system has high real-time performance and flexibility. |
| Oral Session: | COM 02-2 (Paper ID: 9216) |
| Title: | Analysis of Power Consumption in Wireless Sensor Networks |
| Author: | Sami Salah and Xiaohong Shen |
| Affiliation: | School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shaanxi, China. |
| Abstract: | It is quite important to learn the power consumption in a wireless sensor network (WSN) since its determinate the lifetime of the entire WSN. This paper analyzes the power consumption and efficiency of terminal devices, coordinators and the entire WSN in a real WSN system with CC2530 transceiver. It was revealed that the lifetime of an WSN depends on the information collection, working algorithm, etc. The research result lays a foundation for the lifetime estimate in an WSN. |
| Oral Session: | COM 02-3 (Paper ID: 9088) |
| Title: | Rate Analysis of Ad Hoc Networks under Rapid On-Off-Division Duplex |
| Author: | Meng Yu and Wenyi Zhang |
| Affiliation: | Department of EEIS, University of Science and Technology of China, Hefei, Anhui, China. |
| Abstract: | We examine the deployment of rapid on-off-division duplex (RODD) scheme, a paradigm to enable bidirectional communication with half-duplex radios, in a partially-connected ad hoc network. Different from symmetric interlinked ad hoc network, not all the received signals can be decoded by receivers in partially connected networks, thus the effect of multi-user interference should be considered and the throughput of such network is evaluated with Gaussian code-books and random on-off masks. Numerical experiments show that the throughput of RODD is higher than that of the random access protocol in 802.11b. However, the throughput is shown to be limited as the number of users and the probability of transmission increase. Based on error-control codes and compressive sensing, a general paradigm for on-off mask generation and channel coding is discussed. |
| Oral Session: | COM 02-4 (Paper ID: 9049) |
| Title: | Frequency Channel Equalization Based on Variable Step-Size LMS Algorithm for OFDM Underwater Communications |
| Author: | Zeping Sui and Shefeng Yan |
| Affiliation: | Institute of Acoustics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China. |
| Abstract: | In this paper, we intend to improve the performance of the least mean square (LMS) channel equalization in terms of bit error rate (BER) and mean square error (MSE) for orthogonal frequency division multiplexing (OFDM) underwater acoustic (UWA) communications by establishing a nonlinear function relationship between the step-size and the error signal. By ignoring the inter-symbol interference (ISI), we propose to consider the frequency LMS channel equalizer in OFDM communication systems as a combination of many parallel single tap frequency domain sub-equalizers, and thus each sub-carrier is individually equalized. The proposed method improves the equalization performance sufficiently in comparison with the existing ones by using large step-sizes initially to improve the convergence rate and small step-sizes that change slowly to match with small error signals. Simulation results demonstrate the superiority of the proposed method. |
| Oral Session: | COM 02-5 (Paper ID: 9087) |
| Title: | Low-Complexity Wake-up Detector for Underwater Acoustic MODEM |
| Author: | Shengjun Xiong, Lisheng Zhou, Qiming Ma, Pengyu du, Wang Chao and Xiaohui Zhu |
| Affiliation: | Science and Technology on Sonar Laboratory, Hangzhou Applied Acoustic Research Institute, Hangzhou, Zhejiang, China |
| Abstract: | Underwater acoustic MODEMs are usually powered by batteries, it is very important to design a low-power wake-up detector to save the power of modems. This paper proposes a low-complexity wake-up detector for underwater acoustic MODEM. A balanced Gold sequence is used to design a two-phase code signal as the wake-up signal. A detector algorithm is proposed that requires only one addition, one subtraction and two multiplication operations for each sample, thus achieving low computational complexity, at the same time, the algorithm can also provide accurate Doppler estimation and rough arrival time estimation for the wake-up signal. The proposed wake-up detection algorithm has been successfully tested in the lake experiment, the results show that, the proposed detector achieves high detection rate and low false alarm rate. Therefore it is suitable as a low-power wake-up detector for underwater acoustic MODEM. |
| Oral Session: | COM 02-6 (Paper ID: 9235) |
| Title: | Hybrid Time-Frequency Domain Turbo Equalization for Single Carrier MIMO Underwater Acoustic Communication |
| Author: | Qianqian Dang1,2, Han Wang1,2, Lianyou Jing3, Yang Zhang1,2 and Chengbing He1,2. |
| Affiliation: | 1. Research and Development Institute, Northwestern Polytechnical University in Shenzhen, Shenzhen, China; 2. School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, China; 3. School of Information and Communication Engineering, Dalian University of Technology, Dalian, China. |
| Abstract: | Shallow seawater acoustic channel has serious multipath effect. In order to improve the quality of underwater acoustic communication, we proposed hybrid time-frequency domain Turbo equalization (HTFDTE) and bidirectional time-frequency domain Turbo equalization (Bi-HTFDTE) for multiple-input multiple-output (MIMO) single carrier (SC) underwater acoustic system with PN code. At the receiving end, the channel is estimated using the known PN code. The frequency domain equalization based on minimum mean square error (MMSE) criterion and the time domain Turbo iterative processing are combined together to further improve performance. To eliminate error propagation effect, the Bi-HTFDTE includes two parallel HTFDTE structures, which requires roughly twice as many computational operations per iteration as the HTFDTE but acheving a lower bit error rate (BER). The simulation results show that the performance of HTFDTE is better than frequency domain Turbo equalization (FDTE). At the order of 10-4, the HTFDTE with three iterations gains about 0.5dB and 1dB over the HTFDTE with first iteration and the FDTE with first iteration for QPSK modulation, respectively. The Bi-HTFDTE with three iterations gains about 0.15dB over the HTFDTE with three iterations. |
| COM Session 03 | |
| Room: D | |
| Time: 13:30~15:30, Saturday, September 21, 2019 | |
| Session Chair: Lingling Zhang, Northwestern Polytechnical University | |
| Oral Session: | COM 03-1 (Paper ID: 9225) |
| Title: | Weighted Factor Graph Aided Distributed Cooperative Position Algorithm |
| Author: | Xingxing Zhu1,2, Yi Zhang1, Chengkai Tang1 and Jun Liu1 |
| Affiliation: | 1.School of Electronics and Information, Northwestern Polytechnical University, Xi’an, Shaanxi, China;2. Shaanxi Key Laboratory of Integrated and Intelligent Navigation, Xi’an, Shaanxi, China. |
| Abstract: | With the development of wireless location technology, related services have been popularized in all walks of life, but the traditional localization has poor robustness and low positioning accuracy when the number of anchors is small and the nodes have position ambiguity. In this paper, a distributed cooperative position technique based on weighted factor graph is proposed. Under the premise of fully considering the cooperative nodes ranging error and the coordinated terminal position ambiguity, combining the factor graph and the sum product algorithm, the belief information transfer model is established, and the information from the neighbor nodes is weighted, after the information converges iteratively. The belief information of agents is obtained. The proposed algorithm is compared with the existing LS co-localization algorithm and ML co-localization algorithm in terms of convergence speed, computational complexity and positioning accuracy. The simulation results show that the positioning accuracy of more than 90% agents in the proposed method can reach 3m under the given parameters, and the positioning performance is much better than the other two algorithms. |
| Oral Session: | COM 03-2 (Paper ID: 9043) |
| Title: | Research on VLF Field Strength Prediction System Based on MapX |
| Author: | Guangming Li1, Xiaolei Sun1, Lin Mao2 |
| Affiliation: | 1. Department of Navigation, Observation and Communication, Navy Submarine Academy, Qingdao, Shandong, China; 2. Troops 92196, Qingdao, Shandong, China. |
| Abstract: | VLF communication is affected by environmental factors, which results in obvious three-dimensional non-uniformity of time, space and frequency, and easily leads to poor command of underwater platforms. Utilizing the predictability of VLF wave propagation, the signal field intensity can be predicted, and the communication effect can be predicted accurately, which can improve the communication efficiency of underwater platform. This paper presents a series of fundamental ideas, function design and implementation of VLF communication signal field strength prediction system based on MapX technology and waveguide mode theory. The practical application shows that the predicted results of the system are in good agreement with the measured data and have high engineering application value. |
| Oral Session: | COM 03-3 (Paper ID: 9045) |
| Title: | Adaptive I/Q Imbalance Compensation Based on Constrained Optimization |
| Author: | Xuan Wang, Qing hui Song and Shubo Dun |
| Affiliation: | The 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang, Hebei, China. |
| Abstract: | A novel adaptive I/Q Imbalance correction algorithm called adjacent quadrature constrained optimization (AQCO) is proposed in this paper. Based on the analysis of diverse sources and factors of I/Q imbalance for a surveillance and reconnaissance receiver, this new method is given to conquer the challenges had not been fully discussed in traditional Look-Up-Table (LUT) or other compensation methods, which regarding the imbalance fluctuation due to limited signal-to-noise ratio (SNR) or the variation of temperature that can not be ignored in practical scenarios. Simulation is conducted to demonstrate the effectiveness of this algorithm in multi-uncooperative signals case with the image frequency successfully being suppressed below the noise floor under the situations that the SNR varies between 10 to 50 dB. |
| Oral Session: | COM 03-4 (Paper ID: 9140) |
| Title: | An Energy-Efficient Transmission Scheme for Buffer-Aided UAV Relaying Networks |
| Author: | Dongju Cao1, Zhifu Yin2, Wendong Yang1 and Guoqin Kang3 |
| Affiliation: | 1. College of Communications Engineering, PLA Army Engineering University, Nanjing, Jiangsu, China; 2. The First Information Sustainment Brigade of Eastern Theater Command Army; 3. Information Communication Academy of National University of Defense Technology, Wuhan, Hubei, China |
| Abstract: | Limited battery capacity is one of the critical issues affecting the network lifetime of unmanned aerial vehicles (UAVs) because of its battery power supply. In this paper, an energy-efficient transmission scheme for buffer-aided UAV relaying networks is proposed. The relays are mounted on UAVs, which use buffers to store the received information and forward it to the destination when the channel quality is good. In particular, we consider adaptive link selection and adaptive power control for the considered network based on the channel state information (CSI), the buffer state and the remaining energy of UAVs. The transmit power is determined according to the amount of information in the buffer, and a threshold value of the transmit power is set to avoid the exponential growth of the transmission power caused by too much information in the buffer. Simulation results show that compared to conventional relaying protocols, the proposed scheme can improve the energy efficiency of buffer-aided UAV relaying networks and make a good trade off between the network lifetime and the average throughput. |
| Oral Session: | COM 03-5 (Paper ID: 9159) |
| Title: | COPO: A Context Aware and Posterior Caching Scheme in Mobile Edge Computing |
| Author: | Peiyan Yuan, Xiaoyan Zhao, Baofang Chang and Yunyun Cai |
| Affiliation: | School of Computer and Information Engineering, Henan Normal University, Xinxiang, Henan, China. |
| Abstract: | Mobile edge caching provides a feasible solution to alleviate the heavy traffic through Device-to-Device (D2D) communication in cellular networks. By integrating the storage capacity of mobile user terminals (UT) and small base stations (SBS), we propose COPO, a COntext aware and Posterior caching scheme, instead of the traditional prior-caching scheme, which assigns contents in advance and then evaluates the system performance. COPO first defines a placement incidence matrix and uses the hit rate metric to study posterior-caching model, and then analyzes the copies of contents derived from the global initial allocation. After that, it places contents and their copies in appropriate nodes with a heuristic algorithm. Consecutively, numerical results are presented to compare the COPO with other caching schemes and show its efficiency and effectiveness. |
| Oral Session: | COM 03-6 (Paper ID: 9199) |
| Title: | Virtual Channel Optimization Downlink NOMA with High-Order Modulations without CSIT |
| Author: | Wenlong Xia, Yuanping Zhou, Qinggong Guo and Qingdang Meng |
| Affiliation: | School of Electronic and Information Engineering, Sichuan University, Chengdu, Sichuan, China. |
| Abstract: | This paper presents a virtual channel optimization (VCO) method for downlink non-orthogonal multiple access (NOMA) systems on high-order modulations up to 16-QAM. With this VCO scheme, we present a new optimization criterion based on maximizing the minimum Euclidean distance among superposition constellation’s points without channel state information at the transmitter (CSIT). Prior works on VCO scheme only focus on quadrature phase-shift keying (QPSK) modulations and the analytical solutions are obtained. However, the analytical solution is challenging to obtain for high-order modulations. We exploit the particle swarm optimization (PSO) algorithm to search the optimal solution. Simulation results for high-order modulations demonstrate the improvement of the overall throughput based on the merit of constellation constrained capacity (CCC). |
| COM Session 04 | |
| Room: D | |
| Time: 16:00~18:00, Saturday, September 21, 2019 | |
| Session Chair: Zhenhua Yu, Xi’an University of Science and Technology | |
| Oral Session: | COM 04-1 (Paper ID: 9020) |
| Title: | Design of Naturally Distorted Image Database-NDID |
| Author: | Guoxiang Zeng and Ping Shi |
| Affiliation: | College of Information Engineering, Communication University of China, Beijing, China. |
| Abstract: | The rich content of the electronic images challenge the existing image quality assessment (IQA) models and image aesthetics assessment models. In the meanwhile, it is difficult to get undistorted images, which is important in traditional databases. Therefore, establishing new database containing naturally distorted images is in urgent need. This database contains both image quality factors and image aesthetics factors, which can meet the future research needs of these two types of models. In this paper, we completed the following tasks majorly: (1) We collected 807 naturally distorted images of four semantics in three ways. (2) A subjective evaluation experiment was designed to allow subjective evaluators to rate and label the distorted images comprehensively. (3) We apply NDID to various kinds of image evaluation models and popular deep learning networks. As experimental results showing, NDID have achieved a flat or slightly lower performance compared with other existing databases used in these models. This even or poor performance indicates that NDID has certain practical value for the improvement of images evaluation models. |
| Oral Session: | COM 04-2 (Paper ID: 9138) |
| Title: | A New Personnel Identification and Position Estimation Algorithm Using Binocular Camera |
| Author: | Chaohui Wu, Yimei Zhang, Mengwei Yang, Bin Kang and Jun Yan |
| Affiliation: | College of Communication & Information Engineering, Nanjing University of Posts & Telecommunications, Nanjing, Jiangsu, China. |
| Abstract: | With the increased requirement of position information for indoor environment, image based indoor localization has received much attentions, since it has low cost, no electromagnetic interference and green environmental protection. In this paper, a new personnel identification and position estimation algorithm using the images from binocular camera is proposed. In the off-line phase, the face image based training data set is used for classification learning by the convolutional neural network (CNN). The personnel identification based classification model is obtained. Then, the depth information obtained from the image are used for distance based regression learning by support vector machine (SVM). The distance based regression model is obtained. In the on-line phase, when the image and its depth information are obtained from the binocular camera, the personnel identification and the distance estimation can be obtained from the personnel identification based classification model and the distance based regression model respectively. Experiment results shown that under the largest number of training data condition, the accuracy of the personnel identification can reach to 91%. Moreover, the average error for distance estimation is less than 5cm. |
| Oral Session: | COM 04-3 (Paper ID: 9160) |
| Title: | Facial Expression Recognition Based on Global and Local Feature Fusion with CNNs |
| Author: | Shengtao Gu1,2, Chao Xu1,2 and Bo Feng1,2 |
| Affiliation: | 1. School of Electronics and Information, Engineering, AnHui University, HeFei, Anhui, China; 2. AnHui Engineering laboratory of Agro-Ecological Big Data, HeFei, Anhui, China. |
| Abstract: | The facial expression recognition is a hot research subject of computer vision, which causes a broad range of application in the domains of human-computer interaction, security and robotics. However, due to the influence of illumination and posture, real-time facial recognition is still a challenge. In this work, a facial expression recognition method based on the parallel convolutional neural network is proposed. Firstly, the face region is extracted from the pre-processed image by the face detector, in accordance with the detected feature points, the face image is cropped into three parts: eyes, noses and mouths. Then, Two CNNs were trained on the original and cropped data sets individually. Finally, the output of the two CNNs is gathered together to complete the classification of the expression. The modified AlexNet, VGGNet and ResNet were used to verify the method on the FER2013 data set. The recognition accuracy of the three models reached 66.672%, 69.407% and 70.744%, respectively. Experiments show that this method has a positive outcome on the recognition of expressions. |
| Oral Session: | COM 04-4 (Paper ID: 9196) |
| Title: | Distributed Generation Grid-Connected Method Based on Big Data Analysis |
| Author: | Zhen Zhang1, Cunxu Wang1, Kaifan Yang1, Tong Wu1 and Tian Yao2 |
| Affiliation: | 1. Electric Power Institute, Shenyang Institute of Engineering, Shenyang, Liaoning, China; 2. Wenshan Power Supply Bureau, China Southern Power Grid Company Limited, Wenshan, Yunnan, China. |
| Abstract: | The large-scale integration of distributed PV into the distribution network will pose challenges to grid security. How to dissipate distributed PV power generation is particularly important. Aiming at the incomplete information of distribution network, a distributed generation grid connected method based on big data analysis is proposed. The historical data of each link in the grid system is integrated, and the distributed power grid-connected capability analysis model is proposed. Considering the adjustment ability of different grid configuration modes, the voltage deviation and voltage fluctuation index are taken as the target value for quantitative calculation, and the safety indexes such as short-circuit current and branch current-carrying flow are taken as constraints, and the acceptance ability is analyzed. Finally, the effectiveness and feasibility of the proposed method are verified by the actual distribution network. The results show that the energy storage configuration is more obvious on the grid side than on the distributed generation side. Distributed PV consumption capacity can be greatly improved. |
| Oral Session: | COM 04-5 (Paper ID: 9200) |
| Title: | A Neural Network Aided Integrated Navigation Algorithm Based on Vehicle Motion Mode Information |
| Author: | Zhidong Zhang1, Falin Wu1, Yushuang Liu2, Yuan Zuo1 and Yinglin Ji1 |
| Affiliation: | 1.SNARS Research Group, School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China; 2. Electro-mechanic Engineering, Beijing, China. |
| Abstract: | For traditional integrated navigation system based on SINS/GNSS, the integrated navigation system will work in standalone inertial navigation when GNSS signals are lost. In this situation, the divergence of SINS error is fast without GNNS information correction. Besides, the divergence of SINS error is related to the motion mode of the vehicle. This paper proposes a BP neural network (BPNN) aided integrated navigation method based on vehicle motion learning. The inputs of the neural network are 10-dimension, including the outputs of the IMU, the three attitude angles estimated by SINS, and the GNSS interruption lasting time. The outputs are three predictions of SINS position error. When GNSS is effective, the neural network is used to learn the SINS error divergence characteristics under several basic motion modes of the vehicle. When the GNSS signal is disturbed, the neural network is used to correct the position error of the SINS to improve the navigation accuracy. Finally, the effectiveness of the algorithm is verified by using an 8-shape motion of the vehicle. |
| Oral Session: | COM 04-6 (Paper ID: 9152) |
| Title: | Generalized Unambiguous Acquisition Technique for BOC Modulated Signals |
| Author: | Zhe Xue, Jianing Wang and Feng Yan |
| Affiliation: | Xi’an Modern Control Technology Research Institute, Xi’an, Shaanxi, China. |
| Abstract: | The multiple side-peaks characteristic of the auto-correlation function always returns an ambiguous acquisition result for the binary offset carrier (BOC) modulated signal. To solve this problem, based on the analysis of the auto-correlation function of BOC signal, a new unambiguous acquisition algorithm is proposed for BOC signals. Firstly, the sub-carrier is decompose into many sub-waves according to the signal type，then the correlation result with single peak is constructed according to the combination of the sub-correlation result, finally the general unambiguous acquisition method based on the correlation multiplication cancellation technique is proposed. Theoretical analysis and simulation results show that the proposed algorithm can deal with all kinds of BOC modulated signals, and its detection performance outperforms the other comparison unambiguous acquisition methods in this paper |
| COM Session 05 | |
| Room: C | |
| Time: 13:30~15:30, Sunday, September 22, 2019 | |
| Session Chair: Feiyun Wu, Northwestern Polytechnical University | |
| Oral Session: | COM 05-1 (Paper ID: 9158) |
| Title: | A System Modeling Method of AUV Swarms Based on UPDM |
| Author: | Chang Cai1, Jianfeng Chen1, Juan Lei1,2 |
| Affiliation: | 1. School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shaanxi, China; 2. Xi’an Tianhe Maritime Technologies Co., Ltd, Xi’an, Shaanxi, China. |
| Abstract: | Aiming at the typical underwater search and rescue task of AUV swarm, this paper establishes an integrated AUV swarm model on underwater target characteristics, underwater acoustic and optical equipment performance, underwater environment, etc. The task scheduling is based on the integrated AUV swarm model. Moreover, this paper proposes a construction method of AUV swarm task scheduling system by combining task scheduling of AUV swarm with DoDAF architecture framework. In addition, the UPDM is used to verify and analyze the proposed method, and the visiuable task scheduling system is executed and displays in 3D video form. It is shown that the integrated modeling of the AUV swarm is all-round and necessary, and the UPDM provides a suitable simulation platform and efficiency evaluation tool for AUV swarm task scheduling. |
| Oral Session: | COM 05-2 (Paper ID: 9126) |
| Title: | Divided Localization of Multiple Targets Based on Compressive Sensing Algorithm |
| Author: | Shanbin Li and Tongjie Chen |
| Affiliation: | School of Automation Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China. |
| Abstract: | This paper is concerned with the multi-target localization based on compressive sensing (CS). If orthogonal matching pursuit (OMP) is applied as the signal reconstruction algorithm to locate targets, there will always be a situation that only part of targets are located successfully. To solve this problem, divided localization of multiple targets is proposed. In data preparation stage, the results of single and multiple localization are calculated under two kinds of partitioning granularity. Then, in divided localization stage, according to the data from data preparation stage, part of targets can be predetermined by finding the clusters. Also, the remaining targets can be located in the possible falling area. Finally, simulation results are provided to demonstrate that, compared with other schemes, the proposed algorithm obviously improves the positioning accuracy and the anti-noise ability. |
| Oral Session: | COM 05-3 (Paper ID: 9061) |
| Title: | Sparse Bayesian Learning for Blind Multichannel Estimation in Shallow Water |
| Author: | Wei Feng1,2 and Jianlong Li1,2 |
| Affiliation: | 1. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, Zhejiang, China; 2. Key Laboratory of Ocean Observation-Imaging Testbed of Zhejiang Province, Zhoushan, Zhejiang, China. |
| Abstract: | Blind channel estimation (BCE) has been used in various underwater acoustic applications, with the aim to deconvolve the channel impulse response (CIR) from the received signals without a priori knowledge of the source signal. This paper develops a blind multichannel estimation method implemented with a sparse Bayesian learning (SBL) algorithm. The proposed approach exploits the cross relations (CR) between a channel output pair and the multipath sparsity. The SBL scheme for channel estimation can automatically select the sparse impulse responses by maximizing the evidence. Simulations are performed in shallow water environment and the results confirm the effectiveness of the proposed method. |
| Oral Session: | COM 05-4 (Paper ID: 9184) |
| Title: | Compressive Impulse Response Sensing of the Sparse Channel in Multipath Environments |
| Author: | Feiyun Wu1, Kunde Yang1, Tian Tian1, Feng Tong2 and Yang Hu3 |
| Affiliation: | 1. School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shaanxi, China; 2. MOE Key Lab of UWAcom and Marine information Technology, Xiamen University, Fujian, China; 3. School of Information and Communication Engineering, Dalian University of Technology, Dalian, Liaoning, China. |
| Abstract: | Channel impulse response (CIR) in noisy multipath environments can be obtained based on the least squares criterion. However, the CIR obtained is contaminated by pseudo paths. By exploiting the sparse structure of a sparse channel in multipath environments, this work presents an approach for compressed sensing that uses the Gram-Schmidt algorithm to find orthogonal bases (Gram-Schmidt matching pursuit, GSMP), which leads to a fast, orthogonal way of selecting the supports for the dictionaries. The probe signal is used to construct the dictionary matrix, whose column vectors are selected as the supports. The selected supports from dictionary matrix and the noisy received signal are used for recovering the CIR. The simulation results confirm that the proposed GSMP method, compared to LS, MP, CoSaMP, ROMP methods, provides superior performance in terms of mean square error (MSE). |
| Oral Session: | COM 05-5 (Paper ID: 9185) |
| Title: | Mean Doppler Compensation for SIMO Turbo Equalization in Underwater Acoustic Communications |
| Author: | Zhenduo Wang, Zhe Xie, Wu Zhou and Hongtao Zhang |
| Affiliation: | Science and Technology on Sonsar Laboratory, Hangzhou Applied Acoustic Research Institute, Hangzhou, Zhejiang, China. |
| Abstract: | Underwater acoustic (UWA) communication is a major tool for underwater wireless data transmission. UWA communications with multiple receivers, as vertical receive arrays could utilize space diversity to improve system reliability. For equalization, direct-adaptive turbo equalization (DA-TEQ) uses the exchange of extrinsic information between equalizer and decoder to improve system performance. However, due to the distance between adjacent receive array, each hydrophone of the whole receive array may have different Doppler spreads, which need to be carefully processed. In this paper, a mean Doppler compensation strategy for multi-array UWA communications is proposed for UWA communication signal equalization. The Doppler spread is estimated for each hydrophone separately, and mean Doppler spread is calculated prior to compensate the Doppler spread for the received signal to correct the carrier phase distortion for each receiving hydrophone. Afterwards, time-reversal is performed for multichannel combination, and directive-adaptive turbo equalization (DA-TEQ) is applied for symbol recovery. The proposed mean Doppler compensation strategy is verified by lake experiment results. |
| Oral Session: | COM 05-6 (Paper ID: 9170) |
| Title: | Adaptive Stochastic Resonance Aided Demodulation for the Challenge of Deepwater Extremely Vertical Acoustic Communication |
| Author: | Xueyi Jin1, Qixuan Sun2, Linsong Song1, Chunyan Zhao3 and Xiaohong Shen2 |
| Affiliation: | 1. Drilling R&D Institute, China Oilfield Services Limited, Sanhe, Hebei, China; 2. School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shanxi, China; 3. Drilling R&D Institute, China Oilfield Services Limited, Zhanjiang, Guangdong, China. |
| Abstract: | In this paper, we propose a binary frequency shift keying (2FSK) demodulation method via adaptive frequency scaling stochastic resonance (AFS-SR), aiming to improve reliability of deep water extremely vertical acoustic communication. Through the sea trial experiment, we prove the greatest problem of vertical acoustic channel is the significantly amplitude fading of the signal. And the amplitude fading of the signal is more severe, when the underwater acoustic is transmitted from negative gradient to positive gradient. For verifying the reliability performance of the proposed approach, a simulated comparison with traditional 2FSK coherent and non-coherent demodulation is conducted. And computer simulation results indicate that, the method proposed exhibits better bit error rate (BER) performance than traditional methods in low signal-to-noise ratio (SNR). Moreover, for the BER value of 10−3, the method we proposed provides approximately 11dB better BER performance than traditional demodulation. The result demonstrates that the proposed method has a good application prospect in vertical acoustic channel. Therefore, it is extremely helpful to develop the level of riser safety monitoring for deep water drilling riser. |
| CPT Session 01 | |
| Room: P | |
| Time: 08:30~10:15, Sunday, September 22, 2019 | |
| Session Chair: Ray Cheung, City University of Hong Kong | |
| Oral Session: | CPT 01-1 (Paper ID: 9210) |
| Title: | GPADRlex: Grouped Phrasal Adverse Drug Reaction lexicon |
| Author: | Hammad Farooq and Hammad Naveed |
| Affiliation: | Computational Biology Research Lab, Department of Computer Science National University of Computer and Emerging Sciences, Islamabad, Pakistan. |
| Abstract: | Identification and monitoring of adverse drug reactions (ADRs) of marketed drugs from digital media can complement traditional pharmacovigilance activities. A phrasal lexicon is the need of systems that would monitor the ADRs from digital media. In this study, we compiled a large phrasal lexicon from the FDA Adverse Event Reporting System (FAERS) that is specific for ADRs, descriptive in nature and wherein the phrases representing the same ADR are grouped together using semantic similarity based hierarchical clustering. We explored six different methods to compute the phrasal semantic similarity and seven different linkage methods. We compared our automatic clustering with manually curated clusters on a subset of a previous ADR lexicon. Our results show that nine clustering schemes produced significantly better clusters than random clustering. Moreover, we provide a mechanism to generate user-defined k clusters from the 19,585 phrasal ADRs in our lexicon. |
| Oral Session: | CPT 01-2 (Paper ID: 9163) |
| Title: | Blockchain – From Cryptocurrency to Vertical Industries - A Deep Shift |
| Author: | Muhammad Imran Sarwar, Kashif Nisar and Amna Khan |
| Affiliation: | Faculty of Computer Science & IT The Superior College, Lahore, Pakistan. |
| Abstract: | A technology that has shifted the entire paradigm of computer applications during the last decade is undoubtedly, the Blockchain technology. The purpose of inventing Blockchain was to develop a technology in which data is immutable, confidential and located on a de-centralized network. This technology was first used to build a cryptocurrency application, which is just one of many applications developed using Blockchain technology. Since, most of the emphasis has been on the money and finance related services, now the vertical industries have also started to implement Blockchain. This study contributes to review the opportunities of using Blockchain technology in vertical industries. |
| Oral Session: | CPT 01-3 (Paper ID: 9133) |
| Title: | Volume calculation From Three Point Cloud Weights Generated By Semantic Segmentation Of A Solid Object From Multiple Views Of Image Of The Object |
| Author: | Radhamadhab Dalai and Kishore Kumar Senapati |
| Affiliation: | Computer Science & Engg, Birla Institute of Technology Ranchi, India. |
| Abstract: | Regenerating three dimensional point cloud for an object in image has found many applications in used in many computer vision systems. In this paper a deep learning base d semantic segmentation has been used to find region of interest in image. Earlier 3D reconstruction methods have been experimented and tested only for uniform backgrounds, which is disadvantageous for the applications on real images which consists of complex nonuniform regions. In this work semantic segmentation has been used to partition the regions into similar instance based regions. We have used UNET model for the region based segmentation. Then using encoder-decoder scheme the 3D point cloud has been generated after merging pixel clouds. This paper proposes an end-to-end efficient generation network, which is composed of an encoder, a 3D image model, and a decoder. First, a single-view image of object and a nearest-shape retrieval has been formed from UNET are fed into the network; then, the two encoders are merged adaptively according to their homo-graphic or similarity in nature. Then decoder generates fine-grained point clouds from the pixel clouds generated from multiple view images. Each point in the cloud represents a weight according the intensity and color information from which the density and volume of object has been calculated. The experiments on uniform background images show that our method attains accuracy 12 to 15 %margin compared with volumetric and point set generation methods particularly toward large solid objects, and it works multiple view angles as well. |
| Oral Session: | CPT 01-4 (Paper ID: 9211) |
| Title: | Research and Implementation of Intelligent Workshop IoT Cloud Platform Based on Micro-services |
| Author: | Ningning Cui1, Yi Hu2, Dong Yu2 and Fengyu Han1 |
| Affiliation: | 1. University of Chinese Academy of Sciences Shenyang Institute of Computing Technology, Beijing, China; 2. Shenyang Golding NC & Intelligence Tech Co., Ltd Chinese Academy of Sciences Shenyang, China. |
| Abstract: | In view of the current manufacturing transformation, the Internet of Things is included in the “Strategic Emerging Industry Technology” industry category. The country calls for the application of the Industrial Internet of Things platform to sink into the actual production process. This paper designs the intelligent workshop IOT cloud platform based on micro-services. The workshop IOT cloud platform introduces the architecture design of the platform in detail. The framework is divided into three level: physical data sensing layer, data service layer and business processing layer. In the framework implementation process, role-based user access control is used to achieve user access control of platform resources. Using Nginx to achieve load balancing between resource servers. The successful construction of the platform makes the analysis and processing of a large amount of data in the workshop equipment is presented to the user in order, which is of great significance for realizing the digitization of the workshop. |
| Oral Session: | CPT 01-5 (Paper ID: 9074) |
| Title: | QSWC: Quality based Smart Water Channelization Using Internet of Things (IoT) |
| Author: | Safdar Faheem1, Muhammad Zubair1, Muhammad Inam ul Haq1 and Umer Farooq2 |
| Affiliation: | 1. Department of CS & BI Khushal Khan Khattak University Karak, Khyber Pakhtunkhwa, Pakistan; 2. Department of Computer Science, University of Science & Technology Bannu, Khyber Pakhtunkhwa, Pakistan. |
| Abstract: | Water is an integral part of daily life that directly affects almost every aspect of human life. Unfortunately, today water scarcity is considered the major threat globally and Pakistan in specific. An important reason behind this is the excessive use of water without proper management mechanism. The purpose of water management mechanism is to provide proper amount and quality of water continuously to end-user which makes it necessary to streamline the consumption of water for its true use. Considering advancement in technologies, there is a dire need of intelligent system to ensure the water management in an organized manner. In this research work, a novel Smart Water Channelization (SWC) using the concept of Internet of Things (IoT) is proposed. SWC manages water resources in distributed modus having regional control unit(s) (RCU) connected to Consumer Control Unit (CCU). Implementation is to be carried out through simulation and developing a prototype. The proposed system is advantageous to tackle water related health issues, water management, and improved purpose (drinking, household needs, and etc.) based water consumption considering water quality. |
| CPT Session 02 | |
| Room: P | |
| Time: 13:30~15:30, Sunday, September 22, 2019 | |
| Session Chair: Edward CHEUNG, Hong Kong Polytechnic University | |
| Oral Session: | CPT 02-1 (Paper ID: 9089) |
| Title: | Design of a Miniaturized High Power DPA for 4GHz |
| Author: | Shuyuan Zhang and Shichang Zhong |
| Affiliation: | Nanjing Institute of Electronic Devices, Nanjing, China. |
| Abstract: | The Doherty power amplifier based of GaN HEMT which was applied for 4GHz band was designed and implemented, and the symmetrical Doherty structure was used. The power chip and matching circuit of the main power amplifier were as same as the auxiliary power amplifier. The ceramic chip was used. The whole system was integrated into 23.00mm*21.70mm tube shell by means of ceramic chip and gold wire connection, which improved the integration of Doherty power amplifier. The test results showed that the saturated output power could reach more than 48 dBm, and the drain efficiency of saturated output was more than 55%. Moreover, the drain efficiency was more than 50% when the output power was fell back 6 dBm. Compared with the balanced AB amplifier, the Doherty PA had obvious advantages. In addition, the performance about IMD3 of Doherty was better than that of balanced class AB amplifier in the regression region. |
| Oral Session: | CPT 02-2 (Paper ID: 9114) |
| Title: | S-band High-efficiency Miniaturized Wideband GaN Power Amplifier |
| Author: | Fei Li and Shi-Chang Zhong |
| Affiliation: | Nanjing Electronic Devices Institute, Nanjing, China. |
| Abstract: | A high-efficiency S-band miniaturized internally matched GaN high power amplifier (HPA), developed with 24mm AlGaN/GaN high-electron mobility transistors is presented. The amplifier is designed with load-pull method, with the out network matched to compromise between output power and power added efficiency (PAE). Experimental result show that the class C GaN HPA, with drain voltage of 32 V, can be realized more than 62% PAE and 120W output power over the band of 2.6-3.7 GHz at 3ms pulse-width and 30% duty-cycle. The HPA size is 6.6mm×15mm. |
| Oral Session: | CPT 02-3 (Paper ID: 9097) |
| Title: | All polarization gain enhancing lens Based on Meta-surface |
| Author: | Jie Chen1, Shuai Huang1, Jia Cao1, Qun Wu2 and Xiaobin Tang1 |
| Affiliation: | 1. Laboratory of Electromagnetic Compatibility China Academic Electronic and Information Technology, Beijing, China; 2. Department of Microwave Engineering Harbin Institute of Technology, Harbin, China. |
| Abstract: | Among various flat lens devices, meta-surfaces have presented great performance in a versatile and compact platform for manipulating the polarization, phase and amplitude of microwave. However, most meta-surface could only give the best achievement in the exact polarization. Here, this review propose a new antenna lens which was designed to realize achromatic meta-surface devices successfully enhanced gain of muti-polarization patch antenna. A four polarization gain increasing meta-surface was implemented, which was able to locate in the near field of patch antenna without affecting the polarization character. Moreover, because of meta-surface planar nature, patch antenna lens enable the construction of integrated metamaterial circuits as well as easy coupling with other electronic elements. Through this approach, various flat antenna lens with different polarization gain enhancing devices that were previously impossible can be realized, which will allow innovation in patch antenna application. |
| Oral Session: | CPT 02-4 (Paper ID: 9098) |
| Title: | Holographic Antenna Based on Artificial Modulated Impedance Surface |
| Author: | Shuai Huang1, Bingfang Xie2, Jie Chen1, Jia Cao1, Qun Wu2 and Xiaobin Tang1 |
| Affiliation: | 1. Laboratory of Electromagnetic Compatibility China Academic Electronic and Information Technology, Beijing, China; 2. Department of Microwave Engineering，Harbin Institute of Technology, Harbin, China. |
| Abstract: | In this paper, a two-dimension holographic antenna based on artificial modulated impedance surface operating at 5GHz is proposed. By changing the feeding phase difference between the adjacent one-dimension leaky-wave antennas, continuous beam scanning at two-dimension space can be realized. When the feeding phase difference changes from -90° to 90°, the radiation direction in H-plane changes from -27° to 27°, which makes our design a great practical application in reconfigurable antenna. |
| Oral Session: | CPT 02-5 (Paper ID: 9111) |
| Title: | An Improved Frequency Tracking Algorithm for Frequency Hopping Signals Based on ARMA Model |
| Author: | Jing Ma1, Bin Shi1, Xiaochen Guo2 and Yifan Wang2 |
| Affiliation: | 1. Science and Technology on Special System Simulation Laboratory, Beijing, China; 2. Information and Communication Engineering Department, Harbin Engineering University, Harbin, China. |
| Abstract: | Aiming at the real-time processing problem of frequency hopping signals, a frequency tracking algorithm based on FFT, multi-channel clustering and the autoregressive moving average (ARMA) model is proposed in this paper. First, the algorithm performs FFT processing on the received signal samples and estimates the number of source signals and carrier frequency by clustering method. Second, estimate the model coefficients to construct the ARMA model. Then, predict the signal and estimate the decision threshold. Finally, the frequency hopping is determined according to the error between the predicted value of the signal sample and the true value. The experimental results show that the improved algorithm has higher frequency estimation accuracy than the traditional ARMA algorithm after receiving enough signal samples and has lower computational complexity than the SBL algorithm. |
| CPT Session 03 | |
| Room: P | |
| Time: 16:00~18:00, Sunday, September 22, 2019 | |
| Session Chair: Qunfei Zhang, Northwestern Polytechnical University | |
| Oral Session: | CPT 03-1 (Paper ID: 9095) |
| Title: | Public Cloud Security Protection Research |
| Author: | Wei Wu, Qi Zhang, Yue Wang |
| Affiliation: | Information Security Department The First Research Institute of the Ministry of Public Security, Beijing, China. |
| Abstract: | With the rapid development of cloud computing, public cloud as the main form, the attack value is higher, and security is more difficult. This paper expounds the background and concept of public cloud. Starting from the security threat faced by public cloud, proposed public cloud security protection method, and deeply integrates the cybersecurity classified protection 2.0 standard to provide strong support for public cloud security protection. |
| Oral Session: | CPT 03-2 (Paper ID: 9182) |
| Title: | Design and Application of Cloud Platform Based on OpenStack in Remote Online Collection and Monitoring System of Intelligent Workshop |
| Author: | Fengyu Han1, Yi Hu2, Dong Yu2, Ningning Cui1 and Qiang Fu3 |
| Affiliation: | 1. University of Chinese Academy of Sciences Shenyang Institute of Computing Technology, Beijing, China; 2. Shenyang Golding NC & Intelligence Tech Co., Ltd Chinese Academy of Sciences, Shenyang, China; 3. Tianjin University Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, China. |
| Abstract: | With the development of information technology, network technology, Internet technology, cloud computing technology and so on are more and more widely used in various industries. The traditional industrial automation hierarchy structure is complex and the integration degree is |
| Oral Session: | CPT 03-3 (Paper ID: 9201) |
| Title: | Cloud Services Security Evaluation for Multi-Tenants |
| Author: | Sarah Maroc and Jian Biao Zhang |
| Affiliation: | Beijing Key Laboratory of Trusted Computing, Faculty of Information Technology, Beijing University of Technology, Beijing, China. |
| Abstract: | Cloud computing is witnessing a fast development and widespread adoption due to its cost-effective and resource efficient services. Nevertheless, security risks are not outsourced and remain under both cloud service providers and consumers responsibility. One of the main challenges is how to evaluate the security level of cloud services. Current methods are mostly focused on solving the problem of cloud services evaluation from a single user perspective. However, cloud computing is a multi-tenant environment that serves a large number of tenants with multiple end-users at the same time. This heterogeneity leads to different, and often, conflicting security requirements. In this paper, we propose a multi-tenant cloud services evaluation framework, whereby service selection is carried out per groups of tenants rather than per a single user. To ensure that all tenants’ requirements are satisfied, we first consider the similarity between cloud service providers performances and tenants’ requirements. Tenants’ weights are determined in an objective way based on their risk attitudes and contributions to the overall group decision using fuzzy TOPSIS technique. The final ranking of the alternatives is further guided by consensus analysis process to guarantee a final solution with the highest level of agreement. |
| Oral Session: | CPT 04-4 (Paper ID: 9207) |
| Title: | An integrated mechanism for scheduling scientific workflows in Clouds |
| Author: | Ali Kamran1, Umar Farooq2, Ihsan Rabbi2 and Muhammad Zubair3 |
| Affiliation: | 1. Department of CS&IT, QUSIT, D I Khan, Khyber PK - Pakistan; 2. Dept. of CS, UST Bannu, Bannu, Khyber PK - Pakistan; 3. Dept. of CS&BI, KKKUK, Karak, Khyber PK – Pakistan. |
| Abstract: | Scheduling plays a vital role in the efficient utilization of the available resources in clouds. This paper investigates the capabilities of scheduling algorithms of WorkFlowSim framework for processing scientific workflows. These investigations used four different sizes of workloads each, for, five well-known workflows. It was revealed that none of the existing algorithms is capable of efficiently executing all the four sizes of workload for the complete set of workflows. Different algorithms performed better, when they were applied to various workloads of a particular workflow. This fact was used in developing an integrated mechanism, which is capable of using an existing algorithm that performed well in the past, against the given workload, instead of developing a new algorithm. Evaluation results showed that the proposed mechanism improved in 80% cases while the response in 20% cases was found the same. |
