非高斯杂波中机载多进多出雷达动目标检测

doi:10.19665/j.issn1001-2400.2020.03.004

Abstract

Abstract:

Due to the moving platforms, the clutters in distributed airborne MIMO radar are non-Gaussian and non-homogeneous, which leads to having no independent and identically distributed training data to estimate the clutter covariance matrix. To solve the problem, we propose that the covariance of the clutter should be modeled as an inverse complex Wishart distribution whose average value is a Hadamard product of the covariance matrix taper (CMT) and the clutter Doppler spectrum component. Based on this clutter model, a novel detector combing the Bayesian approach and the generalized likelihood ratio test(GLRT) is proposed. Numerical simulation results show that the proposed detector has a better detection performance compared with two current commonly used non-Bayesian detectors.

Key words: multi-input multi-output radar, moving target detection, generalized likelihood ratio test, Bayesian approach, inverse complex Wishart distributionn

CLC Number:

TN957.51

ZHANG Yanfei,SUN Wenjie,SUN Yumei,MENG Xiangwei,CHEN Xiangguang. Detection of the airborne MIMO radar moving target in the non-Gaussian clutter[J].Journal of Xidian University, 2020, 47(3): 23-31.

Figures/Tables 5

References 22

[1]	LIU J, LIU W J, HAN J W, et al. Persymmetric GLRT Detection in MIMO Radar[J]. IEEE Transactions on Vehicular Technology, 2018. 67(12):11913-11923. doi: 10.1109/TVT.25
[2]	LI J, STOICA P. MIMO雷达信号处理[M]. 黄高明,左炜,刘涛,译. 北京, 国防工业出版社, 2013: 303-342.
[3]	CHONG C Y, PASCAL F, OVERLEZ J P, et al. MIMO Radar Detection in Non-Gaussian and Heterogeneous Clutter[J]. IEEE Journal on Selected Topics in Signal Processing, 2010,4(1):115-126. doi: 10.1109/JSTSP.2009.2038980
[4]	KONG L, LI N, CUI G, et al. Adaptive Bayesian Detection for Multiple-input Multiple-output Radar in Compound- Gaussian Clutter with Random Texture[J]. IET Radar, Sonar and Navigation, 2016,10(4):689-698. doi: 10.1049/iet-rsn.2015.0241
[5]	WANG P, LI H, HIMED B. A Parametric Moving Target Detector for Distributed MIMO Radar in Non-homogeneous Environment[J]. IEEE Transactions on Signal Processing, 2013,61(9):2282-2294. doi: 10.1109/TSP.2013.2245323
[6]	WANG P, LI H, HIMED B. Moving Target Detection Using Distributed MIMO Radar in Clutter with Nonhomogeneous Power[J]. IEEE Transactions on Signal Processing, 2011,59(10):4809-4820. doi: 10.1109/TSP.2011.2160861
[7]	GAO Y C, LI H B, HIMED B. Knowledge-aided Range-spread Target Detection for Distributed MIMO Radar in Non- homogeneous Environments[J]. IEEE Transactions on Signal Processing, 2017,65(3):617-627. doi: 10.1109/TSP.2016.2625266
[8]	LIU J, HAN J W, ZHANG Z J, et al. Target Detection Exploiting Covariance Matrix Structures in MIMO Radar[J]. Signal Processing, 2019,154:174-181. doi: 10.1016/j.sigpro.2018.07.013
[9]	LI H, WANG Z, LIU J, et al. Moving Target Detection in Distributed MIMO Radar on Moving Platforms[J]. IEEE Journal on Selected Topics in Signal Processing, 2015,9(8):1524-1535. doi: 10.1109/JSTSP.2015.2467355
[10]	CHEN P, CAO Z X, CHEN Z M, et al. Off-Grid DOA Estimation Using Sparse Bayesian Learning in MIMO Radar with Unknown Mutual Coupling[J]. IEEE Transactions on Signal Processing, 2019,67(1):208-220. doi: 10.1109/TSP.2018.2881663
[11]	韩金旺, 张子敬, 刘军, 等. 基于贝叶斯的高斯杂波背景下MIMO雷达自适应检测算法[J]. 雷达学报, 2019,8(4):501-509.
	HAN Jinwang, ZHANG Zijing, LIU Jun, et al. Adaptive Bayesian Detection for MIMO Radar in Gaussian Clutter[J]. Journal of Radars, 2019,8(4):501-509.
[12]	LIU J, HAN J W, ZHANG Z J, et al. Bayesian Detection for MIMO Radar in Gaussian Clutter[J]. IEEE Transactions on Signal Processing, 2018,66(24):6549-6559. doi: 10.1109/TSP.2018.2879038
[13]	SANGSTON K J, GINI F, GRECO M S. Coherent Radar Target Detection in Heavy-tailed Compound-Gaussian Clutter[J]. IEEE Transactions on Aerospace and Electronic Systems, 2012,48(1):64-77. doi: 10.1109/TAES.2012.6129621
[14]	WARD J. Space-time Adaptive Processing for Airborne Radar: Lincoln Laboratory Technical Report 1015 [R]. Lexington: MIT Lincoln Laboratory, 1994.
[15]	ZHANG S, HE Z, LI J, et al. A Generalized Covariance Matrix Taper Model for KA-STAP in Knowledge-aided Adaptive Radar[J]. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2016,E99A(6):1163-1170.
[16]	BANDIERA F, BESSON O, RICCI G. Covariance-informed Detection in Compound-Gaussian Clutter without Secondary Data [C]//Proceedings of the 2010 IEEE Sensor Array and Multichannel Signal Processing Workshop. Washington: IEEE Computer Society, 2010: 241-244.
[17]	LIU J, ZHOU S H, LIU W J, et al. Tunable Adaptive Detection in Colocated MIMO Radar[J]. IEEE Transactions on Signal Processing, 2018,66(4):1080-1092. doi: 10.1109/TSP.78
[18]	CHEN P, ZHENG L, WANG X D, et al. Moving Target Detection Using Colocated MIMO Radar on Multiple Distributed Moving Platforms[J]. IEEE Transactions on Signal Processing, 2017,65(17):4670-4683. doi: 10.1109/TSP.2017.2714999
[19]	TANG W G, JIANG H, PANG S X. Low Complexity 3D-OMP Algorithms for DOD DOA and Doppler Frequency Estimation in Bistatic MIMO Radar[J]. International Journal of Electronics, 2019,106(6):816-828. doi: 10.1080/00207217.2019.1570555
[20]	MERIAUX B, ZHANG X, EL KORSO M N, et al. Iterative Marginal Maximum Likelihood DOD and DOA Estimation for MIMO Radar in the Presence of SIRP Clutter[J]. Signal Processing, 2019,155:384-390. doi: 10.1016/j.sigpro.2018.09.034
[21]	宫健, 楼顺天, 郭艺夺, 等. 非平稳噪声下相干信源MIMO雷达角度估计[J]. 西安电子科技大学学报, 2018,45(4):175-180
	GONG Jian, LOU Shuntian, GUO Yiduo, et al. MIMO Radar Angle Estimation for Coherent Sources Under Non-stationary Noise[J]. Journal of Xidian University, 2018,45(4):175-180.
[22]	胡勤振, 杨芊, 苏洪涛, 等. 分布式MIMO雷达双门限GLRT CFAR检测[J]. 西安电子科技大学学报, 2016,43(4):29-33.
	HU Qinzhen, YANG Qian, SU Hongtao, et al. Double-threshold GLRT CFAR Detection in Distributed MIMO Radar[J]. Journal of Xidian University, 2016,43(4):29-33.

目标或天线	速度/(m·s^-1)	方位/(°)	位置/km
目标	30	随机选择	(0,0)
发射天线1	250	65	(-2.85, 6.68)
发射天线2	150	257	(6.03, -6.98)
接收天线1	250	35	(4.65, 5.78)
接收天线2	150	49	(-8.98,-4.93)

Detection of the airborne MIMO radar moving target in the non-Gaussian clutter

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 5

References 22

Related Articles 8

Metrics

Comments

Recommended 10

[1]	WU Yong,ZHENG Wei,NIU Wenlong,YANG Zhen. Robust detection of weak transient signals with changing background [J]. Journal of Xidian University, 2019, 46(4): 159-166.
[2]	HU Qinzhen;YANG Qian;SU Hongtao;ZHOU Shenghua;LIU Ziwei;YANG Yang. Double-threshold GLRT CFAR detection in distributed MIMO radar [J]. Journal of Xidian University, 2016, 43(4): 29-33+85.
[3]	WU Yifeng;WANG Tong;WU Jianxin. Moving target detection for airborne radar under repeater jamming environment [J]. J4, 2014, 41(6): 51-56+154.
[4]	XIA Meng;YANG Xiaoniu. Study of three-channel spaceborne SAR-DPCA moving target detection with the slant-placed baseline [J]. J4, 2012, 39(3): 14-19+26.
[5]	ZHOU Yu;ZHANG Linrang;LIU Nan. Research on Bayesian radar adaptive detection [J]. J4, 2012, 39(1): 28-33.
[6]	ZHU Yan;CUI Yan-peng;ZHAO Guo-qing. Sinusoidal weighted frequency modulation jamming technique against moving target detection radar [J]. J4, 2010, 37(2): 273-278.
[7]	YU Jing;LIAO Gui-sheng. Multi-channel moving target focusing and parameter estimation algorithm [J]. J4, 2009, 36(4): 624-668.
[8]	ZHOU Feng;LI Zhen-fang;BAO Zheng. A new approach to ground moving target detection and location based on two-look processing for the single channel SAR system [J]. J4, 2006, 33(5): 673-677.