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

西安电子科技大学学报 ›› 2020, Vol. 47 ›› Issue (3): 23-31.doi: 10.19665/j.issn1001-2400.2020.03.004

非高斯杂波中机载多进多出雷达动目标检测

张彦飞¹,孙文杰¹(),孙玉梅¹,孟祥伟^1,²,陈祥光^1,³

1.烟台南山学院电气与电子工程系,山东烟台 265713
2.海军航空大学电子信息工程系,山东烟台 264001
3.北京理工大学化学与化工学院,北京 100081

收稿日期:2019-07-08 出版日期:2020-06-20 发布日期:2020-06-19
通讯作者: 孙文杰
作者简介:张彦飞(1966—),男,教授,博士,E-mail: 1458044923@qq.com
基金资助:
国家自然科学基金(61871391);国家自然科学基金(61871392);山东省烟台市“双百计划”人才项目(YT201803)

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

ZHANG Yanfei¹,SUN Wenjie¹(),SUN Yumei¹,MENG Xiangwei^1,²,CHEN Xiangguang^1,³

1. Department of Elecrical and Electronic Engineering, Yantai Nanshan University, Yantai 265713, China
2. Department of Electronic and information Engineering, Naval Aeronautical and Astronautical University,Yantai 264001, China
3. School of Chemical Engineering and Environment,Beijing Institute of Technology,Beijing 100081,China

Received:2019-07-08 Online:2020-06-20 Published:2020-06-19
Contact: Wenjie SUN

摘要/Abstract

摘要：

由于多进多出雷达的机载平台运动,导致机载多进多出雷达的杂波是非高斯的并且是非均匀的,无法获得独立同分布的训练数据来估计杂波的协方差矩阵。为解决这一问题,提出把非高斯杂波的协方差建模为未知随机的且服从逆复威沙特分布的随机过程,其均值建模为杂波协方差矩阵的锐化因子和杂波多普勒谱的阿达马乘积。在此基础上采用贝叶斯方法和广义似然比检验准则,设计了一种新型的自适应检测器。数值仿真结果表明:所设计的检测器的性能要好于目前常用的两种非贝叶斯类检测器。

关键词: 多进多出雷达, 动目标检测, 广义似然比检验, 贝叶斯方法, 逆复威沙特分布

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

中图分类号:

TN957.51

张彦飞,孙文杰,孙玉梅,孟祥伟,陈祥光. 非高斯杂波中机载多进多出雷达动目标检测[J]. 西安电子科技大学学报, 2020, 47(3): 23-31.

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.

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参考文献 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)

非高斯杂波中机载多进多出雷达动目标检测

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

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