非均匀环境下基于知识辅助的扩展目标Wald检测器
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摘要
针对分布式多输入多输出(Multiple Input Multiple Output,MIMO)雷达中运动扩展目标的检测问题,本文首先假设每个发射-接收天线组的干扰信号协方差矩阵为互不相同的随机矩阵,以模拟实际的非均匀工作环境。然后引入知识辅助模型,建立先验信息矩阵,描述非均匀环境下的干扰信号特性,其中所有发射-接收天线组的干扰协方差矩阵服从以先验信息矩阵为基础的逆Wishart分布。在此基础上,设计了一种基于知识辅助的Wald(KA-Wald)检测器。仿真实验表明,在小样本的情况下,本文设计的KA-Wald检测器在检测性能上优于传统Wald检测器。而与已有的基于知识辅助的广义似然比检验(KA-GLRT)检测器相比,检测性能相近,但是计算效率更高。
This paper deals with the problem of detecting the moving range-extended target in the distributed MIMO radar.Firstly,the interference covariance matrices corresponding to different transmit-receive( Tx-Rx) antennas are modeled as random matrices which express nonhomogeneous environments. Then a knowledge-aided model which makes these random matrices share a prior covariance matrix structure is built to simulate the characteristics of clutter and noise in nonhomogeneous environments. On this basis,we design a new knowledge-aided Wald( KA-Wald) detector. Simulation results show that the proposed detector possesses a better detection performance compared with the traditional Wald detector. And relative to the knowledge-aided generalized likelihood ratio test( KA-GLRT) detector,the proposed KA-Wald detector has a similar detection performance but a higher efficiency.
This paper deals with the problem of detecting the moving range-extended target in the distributed MIMO radar.Firstly,the interference covariance matrices corresponding to different transmit-receive( Tx-Rx) antennas are modeled as random matrices which express nonhomogeneous environments. Then a knowledge-aided model which makes these random matrices share a prior covariance matrix structure is built to simulate the characteristics of clutter and noise in nonhomogeneous environments. On this basis,we design a new knowledge-aided Wald( KA-Wald) detector. Simulation results show that the proposed detector possesses a better detection performance compared with the traditional Wald detector. And relative to the knowledge-aided generalized likelihood ratio test( KA-GLRT) detector,the proposed KA-Wald detector has a similar detection performance but a higher efficiency.
引文
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[7]Liu J,Zhang Z,Cao Y,et al.A closed-form expression for false alarm rate of adaptive MIMO-GLRT detector with distributed MIMO radar[J].Signal Process,2013,93(9):2771-2776.
[8]Chong C Y,Pascal F,Ovarlez J P,et al.MIMO radar detection in non-gaussian and heterogeneous clutter[J].IEEE J.Sel.Topics Signal Process,2010,4(1):115-126.
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[10]关键,张晓利,黄勇,等.一种距离扩展目标的稳健检测算法[J].信号处理,2011,27(12):1878-1883.Guan Jian,Zhang Xiaoli,Huang Yong,et al.A Robust Detection Method for Range-spread Targets[J].Signal Processing,2011,27(12):1878-1883.(in Chinese)
[11]邹鲲,廖桂生,李军,等.使用杂波先验信息和参考数据的距离扩展目标检测[J].信号处理,2014,30(2):141-148.Zou Kun,Liao Guisheng,Li Jun,et al.Range Spread Target Detection Using Clutter Prior Information and Reference Data[J].Journal of Signal Processing,2014,30(2):141-148.(in Chinese)
[12]Maio A De,Orlando D.Adaptive radar detection of a subspace signal embedded in subspace structured plus Gaussian interference via invariance[J].IEEE Transaction on Signal Process,2016,64(8):2156-2167.
[13]Gao Yongchan,Li Hongbin,Braham.Knowledge-Aided Range-Spread Target Detection for Distributed MIMO Radar in Nonhomogeneous Environments[J].IEEE Transaction on Signal Process,2017,65(3):617-627.
[14]Wang P,Li H,Himed B.A parametric moving target detector for distributed MIMO radar in non-homogeneous environment[J].IEEE Transaction on Signal Process,2013,61(9):2282-2294.
[15]Maio A De,Farina A,Foglia G.Knowledge-Aided Bayesian Radar Detectors&Their Application to Live Data[J].IEEE Transaction on Aerospace and Electronic System,2010,46(1):170-183.
[2]Li J,Stoica P.MIMO Radar Signal Process[M].Wiley,2009:73-74.
[3]Liu W,Wang Y,Lin J,et al.Adaptive detection without training data in collocated MIMO radar[J].IEEE Transaction on Aerospace and Electronic System,2015,51(3):2469-2479.
[4]Xu L,Li J,Stoica P.Target detection and parameter estimation for MIMO radar system[J].IEEE Transaction on Aerospace and Electronic System,2008,44(3):927-939.
[5]Haimovich A M,Blum R S,Cimini L J.MIMO radar with widely separated antennas[J].IEEE Transaction on Signal Process,2008,25(1):116-129.
[6]He Q,Lehmann N H,Blum R S,et al.MIMO radar moving target detection in homogeneous clutter[J].IEEE Transaction on Aerospace and Electronic System,2010,46(3):1290-1301.
[7]Liu J,Zhang Z,Cao Y,et al.A closed-form expression for false alarm rate of adaptive MIMO-GLRT detector with distributed MIMO radar[J].Signal Process,2013,93(9):2771-2776.
[8]Chong C Y,Pascal F,Ovarlez J P,et al.MIMO radar detection in non-gaussian and heterogeneous clutter[J].IEEE J.Sel.Topics Signal Process,2010,4(1):115-126.
[9]Liu J,Li H,Himed B.Persymmetric adaptive target detection with distributed MIMO radar[J].IEEE Transaction on Aerospace and Electronic System,2015,51(1),372-382.
[10]关键,张晓利,黄勇,等.一种距离扩展目标的稳健检测算法[J].信号处理,2011,27(12):1878-1883.Guan Jian,Zhang Xiaoli,Huang Yong,et al.A Robust Detection Method for Range-spread Targets[J].Signal Processing,2011,27(12):1878-1883.(in Chinese)
[11]邹鲲,廖桂生,李军,等.使用杂波先验信息和参考数据的距离扩展目标检测[J].信号处理,2014,30(2):141-148.Zou Kun,Liao Guisheng,Li Jun,et al.Range Spread Target Detection Using Clutter Prior Information and Reference Data[J].Journal of Signal Processing,2014,30(2):141-148.(in Chinese)
[12]Maio A De,Orlando D.Adaptive radar detection of a subspace signal embedded in subspace structured plus Gaussian interference via invariance[J].IEEE Transaction on Signal Process,2016,64(8):2156-2167.
[13]Gao Yongchan,Li Hongbin,Braham.Knowledge-Aided Range-Spread Target Detection for Distributed MIMO Radar in Nonhomogeneous Environments[J].IEEE Transaction on Signal Process,2017,65(3):617-627.
[14]Wang P,Li H,Himed B.A parametric moving target detector for distributed MIMO radar in non-homogeneous environment[J].IEEE Transaction on Signal Process,2013,61(9):2282-2294.
[15]Maio A De,Farina A,Foglia G.Knowledge-Aided Bayesian Radar Detectors&Their Application to Live Data[J].IEEE Transaction on Aerospace and Electronic System,2010,46(1):170-183.