Subspace detection for range-spread target to suppress interference: exploiting persymmetry in non-homogeneous scenario

doi:10.23919/JSEE.2022.000007

Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (1): 60-71.doi: 10.23919/JSEE.2022.000007

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Subspace detection for range-spread target to suppress interference: exploiting persymmetry in non-homogeneous scenario

Yongchan GAO¹(), Linlin MAO^2,*(), Shengqi ZHU³(), Lei ZUO³()

¹ Department of Electronic Engineering, Xidian University, Xi’an 710071, China
² Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
³ National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China

Received:2020-07-16 Online:2022-01-18 Published:2022-02-22
Contact: Linlin MAO E-mail:ycgao@xidian.edu.cn;maoll@mail.ioa.ac.cn;sqzhu@xidian.edu.cn;lzuo@mail.xidian.edu.cn
About author:|GAO Yongchan was born in 1979. She received her Ph.D. degree in electronic engineering from Xidian University in 2015. From February 2016 to January 2017, she was a postdoctoral research associate with the Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, USA. In March 2017, she joined the Electronic Engineering Department, Xidian University, where she is currently an associate professor. Her research interests include adaptive target detection, multistatic radar, passive sensing, and waveform design and diversity. E-mail: ycgao@xidian.edu.cn||MAO Linlin was born in 1991. She received her Ph.D. degree in signal and information processing from Northwestern Polytechnical University, China in 2018. She is currently a research associate in the Institute of Acoustics, Chinese Academy of Sciences, since 2018. Her research interests include adaptive target detection, array signal processing, and multi-sensor networks. E-mail: maoll@mail.ioa.ac.cn||ZHU Shengqi was born in 1984. He received his Ph.D. degree in electrical engineering from Xidian University in 2010. In 2010 he joined Xidian University as a full assistant professor in the National Laboratory of Radar Signal Processing where he became an associate professor in 2012. His research interests include space-time adaptive processing, SAR ground moving target indication, and sparse signal processing. E-mail: sqzhu@xidian.edu.cn||ZUO Lei was born in 1984. He received his Ph.D. degree from Xidian University in 2014. He is currently an associate professor in the National Laboratory of Radar Signal Processing, Xidian University. His current research interests include target detection, time-frequency analysis and synthesis, and time-frequency rate analysis. E-mail: lzuo@mail.xidian.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (61901467; 61701370), the Aeronautical Foundation of China (20180181001), China Postdoctoral Science Foundation (2019M653561; 2020T130493), the Aerospace Science and Technology Fund (SAST2018-098), and the National Defense Science and Technology Foundation of China (2019-JCJQ-JJ-060).

Abstract

Abstract:

This paper deals with subspace detection for range-spread target in non-homogeneous clutter with unknown covariance matrix where structured interference is presented in the received data. Through exploiting the persymmetry of the clutter covariance matrix, we propose two adaptive target detectors, which are referred to as persymmetric subspace Rao to suppress interference and persymmetric subspace Wald to suppress interference (“PS-Rao-I” and “PS-Wald-I”), respectively. The persymmetry-based design brings in the advantage of easy implementation for small training sample support. The signal flow analysis of the two detectors shows that the PS-Rao-I rejects interference and integrates signals successively through separated matrix projection, while the PS-Wald-I jointly achieves interference elimination and signal combination via oblique projection. In addition, both detectors are shown to be constant false alarm rate detectors, significantly improving the detection performance with other competing detectors under the condition of limited training.

Key words: adaptive detection, range-spread target, persymmetric structure, Rao test, Wald test

Yongchan GAO, Linlin MAO, Shengqi ZHU, Lei ZUO. Subspace detection for range-spread target to suppress interference: exploiting persymmetry in non-homogeneous scenario[J]. Journal of Systems Engineering and Electronics, 2022, 33(1): 60-71.

Figures/Tables 8

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Subspace detection for range-spread target to suppress interference: exploiting persymmetry in non-homogeneous scenario

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