Unique Parameters Selection Strategy of Linear Canonical Wigner Distribution via Multiobjective Optimization Modeling

SHI Xiya; WU Anyang; SUN Yun; QIANG Shengzhou; JIANG Xian; HAN Puyu; CHEN Yunjie; ZHANG Zhichao

doi:10.23919/cje.2021.00.338

Volume 32 Issue 3

May 2023

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SHI Xiya, WU Anyang, SUN Yun, et al., “Unique Parameters Selection Strategy of Linear Canonical Wigner Distribution via Multiobjective Optimization Modeling,” Chinese Journal of Electronics, vol. 32, no. 3, pp. 453-464, 2023, doi: 10.23919/cje.2021.00.338

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SHI Xiya, WU Anyang, SUN Yun, et al., “Unique Parameters Selection Strategy of Linear Canonical Wigner Distribution via Multiobjective Optimization Modeling,” Chinese Journal of Electronics, vol. 32, no. 3, pp. 453-464, 2023, doi: 10.23919/cje.2021.00.338

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Unique Parameters Selection Strategy of Linear Canonical Wigner Distribution via Multiobjective Optimization Modeling

doi: 10.23919/cje.2021.00.338

SHI Xiya^1
,,
WU Anyang^1
,,
SUN Yun^1
,,
QIANG Shengzhou^1
,,
JIANG Xian^1
,,
HAN Puyu^1
,,
CHEN Yunjie^1
,,
ZHANG Zhichao^{1, 2
,}

1.
School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing 210044, China
2.
Faculty of Information Technology, Macau University of Science and Technology, Macau 999078, China

Funds: This work was supported by the National Natural Science Foundation of China (61901223), the Natural Science Foundation of Jiangsu Province (BK20190769), the Jiangsu Planned Projects for Postdoctoral Research Funds (2021K205B), the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (19KJB510041), the Jiangsu Province High-Level Innovative and Entrepreneurial Talent Introduction Program (R2020SCB55), the Macau Young Scholars Program (AM2020015), the Startup Foundation for Introducing Talent of NUIST (2019r024), the Postgraduate Research & Practice Innovation Program of Jiangsu Province, the NUIST Students’ Platform for Innovation and Entrepreneurship Training Program (202110300033Z, 202010300235), and the Six Talent Peaks Project in Jiangsu Province (SWYY-034)

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Author Bio:
Xiya SHI was born in Pizhou, Jiangsu Province, China, in 1998. She received a double B.S. degree in financial mathematics and economic law from Yancheng Normal University, Yancheng, China, in 2020. She is currently pursuing the M.S. degree in mathematics at Nanjing University of Information Science and Technology, Nanjing, China. Her research interests include radar signal processing and time-frequency analysis. (Email: shixiya910@163.com)

Anyang WU was born in Nanjing, Jiangsu Province, China, in 1997. He received the B.S. degree in applied statistics from Nanjing University of Information Science and Technology (NUIST), Nanjing, China, in 2019. He is currently pursuing the M.S. degree in applied statistics at NUIST, Nanjing, China. His research interests include linear canonical transform and statistical signal processing. (Email: wuanyang1122@163.com)

Yun SUN was born in Suzhou, Jiangsu Province, China, in 2001. She is currently pursuing the B.S. degree in information and computer science at Nanjing University of Information Science and Technology, Nanjing, China. Her research interests include computational mathematics and signal processing. (Email: kiyoumis@icloud.com)

Shengzhou QIANG was born in Wuxi, Jiangsu Province, China, in 2001. He is currently pursuing the B.S. degree in information and computer science for embedded training at NUIST, Nanjing, China. During the winter vacation of 2022, he participated in an exchange program on information technology and artificial intelligence at Macau University of Science and Technology, Macau, China. His research interests include signal processing, artificial intelligence, and data science. (Email: qshengz@foxmail.com)

Xian JIANG was born in Liyang, Jiangsu Province, China, in 2000. He is currently pursuing the B.S. degree in information and computer science for embedded training at NUIST, Nanjing, China. From April 2021 to March 2022, he hosted the NUIST Students’ Platform for National Innovation and Entrepreneurship Training Program. His research interests include non-stationary signal processing and computational mathematics. (Email: xianjiang831@foxmail.com)

Puyu HAN was born in Shenyang, Liaoning Province, China, in 2001. He is currently pursuing the B.S. degree in information and computer science at Nanjing University of Information Science and Technology, Nanjing, China. Since 2021, he has been founded the SpaceBased Science and Technology Innovation, and relying on the team he was awarded the Silver Medal of the International Internet Increase Student Innovation and Entrepreneurship Competition. His research interests include ground penetrating radar and image processing. (Email: hanpuyu20010101@126.com)

Yunjie CHEN was born in Yancheng, Jiangsu Province, China, in 1980. He received the Ph.D. degree in pattern recognition and intelligent system from Nanjing University of Science and Technology, Nanjing, China, in 2008. He is currently a Full Professor with the School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, China. Since 2019, he has been hosted the Six Talent Peaks Project in Jiangsu Province. His research interests include pattern recognition, image segmentation, and image processing. (Email: priestcyj@nuist.edu.cn)

Zhichao ZHANG (corresponding author) was born in Jingdezhen, Jiangxi Province, China, in 1991. He received the B.S. degree in mathematics and applied mathematics from Gannan Normal University, Ganzhou, China, in 2012, and the Ph.D. degree in mathematics of uncertainty processing from Sichuan University, Chengdu, China, in 2018. From September 2017 to September 2018, he was awarded a grant from the China Scholarship Council to study as a visiting student researcher with the Department of Electrical and Computer Engineering, Tandon School of Engineering, New York University, Brooklyn, NY, USA. Since 2019, he has been with the School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing, China, where he is currently a Full Professor and Doctoral Supervisor. He is currently working as a Macau Young Scholars Postdoctoral Fellow in information and communication engineering with the School of Computer Science and Engineering, Macau University of Science and Technology, Macau, China. He was a Member of Institute of Electrical and Electronic Engineers, a Member of International Association of Engineers, a Member of China Society for Industrial and Applied Mathematics, a Member of Chinese Institute of Electronics, and a Member of Beijing Society for Interdisciplinary Science. His research interests include the mathematical theories, methods and applications in signal and information processing, including fundamental theories such as Fourier analysis, functional analysis and harmonic analysis, applied theories such as signal representation, sampling, reconstruction, filter, separation, detection and estimation, and engineering technologies such as satellite communications, radar detection and electronic countermeasures. (Email: zzc910731@163.com)
Received Date: 2021-09-12
Accepted Date: 2022-03-10

Available Online: 2022-07-15

Publish Date: 2023-05-05

Abstract

Abstract

There are many kinds of linear canonical transform (LCT)-based Wigner distributions (WDs), which are very effective in detecting noisy linear frequency-modulated (LFM) signals. Among WDs in LCT domains, the instantaneous cross-correlation function type of Wigner distribution (ICFWD) attracts much attention from scholars, because it achieves not only low computational complexity but also good detection performance. However, the existing LCT free parameters selection strategy, namely a solution of the expectation-based output signal-to-noise ratio (SNR) optimization model, is not unique. In this paper, by introducing the variance-based output SNR optimization model, a multiobjective optimization model is established. Then the existence and uniqueness of the optimal parameters of ICFWD are investigated. The solution of the multiobjective optimization model with respect to one-component LFM signal added with zero-mean stationary circular Gaussian noise is derived. A comparison of the unique parameters selection strategy and the previous one is carried out. The theoretical results are also verified by numerical simulations.
- Instantaneous cross-correlation,
- LCT free parameters,
- Multiobjective optimization,
- Stationary circular Gaussian noise,
- Wigner distribution

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References(53)

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