Persymmetric adaptive polarimetric detection of subspace range-spread targets in compound Gaussian sea clutter

doi:10.23919/JSEE.2023.000133

Journal of Systems Engineering and Electronics ›› 2024, Vol. 35 ›› Issue (1): 31-42.doi: 10.23919/JSEE.2023.000133

• RADAR DETECTION AND INTERFERENCE SUPPRESSION • Previous Articles

Persymmetric adaptive polarimetric detection of subspace range-spread targets in compound Gaussian sea clutter

Shuwen XU¹^,*(), Yifan HAO²(), Zhuo WANG³(), Jian XUE⁴()

¹ National Key Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
² Xi’an Electronic Engineering Research Institute, Xi’an 710100, China
³ Beijing Institute of Radio Measurement, Beijing 100039, China
⁴ School of Communications and Information Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710121, China

Received:2022-10-14 Accepted:2023-10-08 Online:2024-02-18 Published:2024-03-05
Contact: Shuwen XU E-mail:swxu@mail.xidian.edu.cn;yf_hao@stu.xidian.edu.cn;kingwz301@sina.com;jxue@xupt.edu.cn
About author:
XU Shuwen was born in 1985. He received his B.E. and Ph.D. degrees in electronic engineering from Xidian University, Xi’an, China, in 2006 and 2011, respectively. He is a professor with the National Key Laboratory of Radar Signal Processing, Xidian University. His research interests are in the fields of radar target detection, time-frequency analysis, and synthetic aperture radar image processing. E-mail: swxu@mail.xidian.edu.cn

HAO Yifan was born in 1997. He received his M.S. degree in information and communication engineering from Xidian University. He is an assistant engineer in Xi’an Electronic Engineering Research Institute. His research interests include polarimetric adaptive detection and sea clutter characteristic analysis. E-mail: yf_hao@stu.xidian.edu.cn

WANG Zhuo was born in 1980. He received his M.S. degree in information and communication engineering from Xidian University. He is a researcher with Beijing Institute of Radio Measurement, Beijing, China. His research interests include radar system design and signal processing. E-mail: kingwz301@sina.com

XUE Jian was born in 1993. He received his B.E. and Ph.D. degrees in electronic engineering from Xidian University, Xi’an, China, in 2015 and 2020, respectively. He is an associate professor with the School of Communications and Information Engineering, Xi’an University of Posts and Telecommunications. His research interests include radar clutter suppression, radar target detection, machine learning, and intelligent radar signal processing. E-mail: jxue@xupt.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (62371382;62071346), the Science, Technology & Innovation Project of Xiong’an New Area (2022XAGG0181), and the Special Funds for Creative Research (2022C61540).

Abstract

Abstract:

This paper focuses on the adaptive detection of range and Doppler dual-spread targets in non-homogeneous and non-Gaussian sea clutter. The sea clutter from two polarimetric channels is modeled as a compound-Gaussian model with different parameters, and the target is modeled as a subspace range-spread target model. The persymmetric structure is used to model the clutter covariance matrix, in order to reduce the reliance on secondary data of the designed detectors. Three adaptive polarimetric persymmetric detectors are designed based on the generalized likelihood ratio test (GLRT), Rao test, and Wald test. All the proposed detectors have constant false-alarm rate property with respect to the clutter texture, the speckle covariance matrix. Experimental results on simulated and measured data show that three adaptive detectors outperform the competitors in different clutter environments, and the proposed GLRT detector has the best detection performance under different parameters.

Key words: sea clutter, adaptive polarimetric detection, compound Gaussian model, subspace range-spread target, persymmetric structure

Shuwen XU, Yifan HAO, Zhuo WANG, Jian XUE. Persymmetric adaptive polarimetric detection of subspace range-spread targets in compound Gaussian sea clutter[J]. Journal of Systems Engineering and Electronics, 2024, 35(1): 31-42.

Figures/Tables 10

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References 31

1	CONTE E, BISCEGLIE M D, GALDI C, et al A procedure for measuring the coherence length of the sea texture. IEEE Trans. on Instrumentation and Measurement, 1997, 46 (4): 836- 841. doi: 10.1109/19.650784
2	GINI F, GRECO M Covariance matrix estimation for CFAR detection in correlated heavy tailed clutter. Signal Processing, 2002, 82 (12): 1847- 1859. doi: 10.1016/S0165-1684(02)00315-8
3	JAVIER C, JAVIER G, ÁLVARO B, et al Statistical analysis of a high-resolution sea-clutter database. IEEE Trans. on Geoscience and Remote Sensing, 2010, 48 (4): 2024- 2037. doi: 10.1109/TGRS.2009.2033193
4	WARD K D Compound representation of high resolution sea clutter. Electronics Letters, 1981, 17 (16): 561- 563. doi: 10.1049/el:19810394
5	CONTE E, LONGO M, LOPS M Modelling and simulation of non-Rayleigh radar clutter. IEE Proceedings F (Radar and Signal Processing), 1991, 138 (2): 121- 130. doi: 10.1049/ip-f-2.1991.0018
6	JEN K J Amplitude distribution of composite terrain radar clutter and the K-distribution. IEEE Trans. on Antennas & Propagation, 1984, 32 (10): 1049- 1062.
7	GRECO M, STINCO P, GINI F Identification and analysis of sea radar clutter spikes. IET Radar, Sonar & Navigation, 2010, 4 (2): 239- 250.
8	FARSHCHIAN M, POSNER F L. The Pareto distribution for low grazing angle and high resolution X-band sea clutter. Proc. of the IEEE Radar Conference, 2010: 789−793.
9	OLLILA E, TYLER D E, KOIVUNEN V, et al Compound-Gaussian clutter modeling with an inverse Gaussian texture distribution. IEEE Signal Processing Letters, 2012, 19 (12): 876- 879. doi: 10.1109/LSP.2012.2221698
10	XUE J, XU S W, LIU J, et al Model for non-Gaussian sea clutter amplitudes using generalized inverse Gaussian texture. IEEE Geoscience and Remote Sensing Letters, 2018, 16 (6): 892- 896.
11	SHI S N, SHUI P L Sea-surface floating small target detection by one-class classifier in time-frequency feature space. IEEE Trans. on Geoscience and Remote Sensing, 2018, 56 (11): 6395- 6411. doi: 10.1109/TGRS.2018.2838260
12	PARK H R, LI J, WANG H Polarimetric-space-time domain generalized likelihood ratio detection of radar targets. Signal Processing, 1995, 41 (2): 153- 164. doi: 10.1016/0165-1684(94)00097-J
13	ANTONIO D M, GIUSEPPE R A polarimetric adaptive matched filter. Signal Processing, 2001, 81 (12): 2583- 2589. doi: 10.1016/S0165-1684(01)00150-5
14	LOMBARDO P, PASTINA D, BUCCIARELLI T Adaptive polarimetric target detection with coherent radar. II. Detection against non-Gaussian background. IEEE Trans. on Aerospace and Electronic Systems, 2001, 37 (4): 1207- 1220.
15	DE M A, ALFANO G, CONTE E Polarimetric diversity detection in compound-Gaussian clutter. IEEE Trans. on Aerospace and Electronic Systems, 2004, 40 (1): 114- 131. doi: 10.1109/TAES.2004.1292147
16	GUAN J, ZHANG Y F, HUANG Y Adaptive subspace detection of range-distributed target in compound-Gaussian clutter. Digital Signal Processing, 2009, 19 (1): 66- 78. doi: 10.1016/j.dsp.2007.12.005
17	XU S W, SHI X Y, XUE J, et al Adaptive subspace detection of range-spread target in compound Gaussian clutter with inverse Gaussian texture. Digital Signal Processing, 2018, 81, 79- 89. doi: 10.1016/j.dsp.2018.07.002
18	SHUAI X F, KONG L J, YANG J Y Performance analysis of GLRT-based adaptive detector for distributed targets in compound-Gaussian clutter. Signal Processing, 2010, 90 (1): 16- 23. doi: 10.1016/j.sigpro.2009.05.008
19	ALFANO G, DE M A, CONTE E Polarimetric diversity detection of distributed targets in compound-Gaussian clutter. IEEE Trans. on Aerospace and Electronic Systems, 2004, 40 (2): 755- 765. doi: 10.1109/TAES.2004.1310021
20	REED I S, MALLETT J D, BRENNAN L E Rapid convergence rate in adaptive arrays. IEEE Trans. on Aerospace & Electronic Systems, 1974, AES-10 (6): 853- 863.
21	PASTINA D, LOMBARDO P, BUCCIARELLI T Adaptive polarimetric target detection with coherent radar. I. Detection against Gaussian background. IEEE Trans. on Aerospace and Electronic Systems, 2001, 37 (4): 1194- 1206.
22	NITZBERG R Application of maximum likelihood estimation of persymmetric covariance matrices to adaptive processing. IEEE Trans. on Aerospace and Electronic Systems, 1980, 16 (1): 124- 127.
23	ZHANG Y X, SHU Q Q, JIANG T A GLRT-based polarimetric detector for sea-surface weak target detection. IEEE Geoscience and Remote Sensing Letters, 2020, 19, 1500705.
24	WANG Z H, HE Z S, HE Q, et al. Persymmetric adaptive CFAR detector in compound Gaussian sea clutter with inverse Gaussian texture. Proc. of the IEEE International Geoscience and Remote Sensing Symposium, 2021: 5000−5003.
25	NOVAK L M, BURL M C Optimal speckle reduction in POL-SAR imagery and its effect on target detection. Proc. of the SPIE Technical Symposium on Aerospace Sensing, 1989, 84- 115. doi: 10.1117/12.960517
26	WAX M, ZISKIND I Detection of the number of coherent signals by the MDL principle. IEEE Trans. on Acoustics, Speech, and Signal Processing, 1989, 37 (8): 1190- 1196. doi: 10.1109/29.31267
27	WAX M Detection and localization of multiple sources in noise with unknown covariance. IEEE Trans. on Signal Processing, 1992, 40 (1): 245- 249. doi: 10.1109/78.157206
28	MA C, NG B P A CFAR based model order selection criterion for complex sinusoids. Signal Processing, 2006, 86 (9): 2296- 2303. doi: 10.1016/j.sigpro.2005.10.012
29	NICOLAS B, KHENCHARF A, GARELLO R GLRT subspace detection for range and Doppler distributed targets. IEEE Trans. on Aerospace and Electronic Systems, 2008, 44 (2): 678- 696. doi: 10.1109/TAES.2008.4560214
30	CUI G L, KONG L J, YANG X B, et al Distributed target detection with polarimetric MIMO radar in compound-Gaussian clutter. Digital Signal Processing, 2012, 22 (3): 430- 438. doi: 10.1016/j.dsp.2011.10.015
31	HAYKIN S. The McMaster IPIX radar sea clutter database. http://soma.crl.mcmaster.ca/ipix/.

Target model	Target cell
Target model	1	2	3	4
M1	0.1	0.1	0.1	0.1
M2	0.1,0.2	0.2	0.2,0.4	0.1,0.2,0.3,0.4

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Persymmetric adaptive polarimetric detection of subspace range-spread targets in compound Gaussian sea clutter

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