CFAR assessment of covariance matrix estimators for non-Gaussian clutter  

作　　者：HE You, JIAN Tao, SU Feng, QU ChangWen & PING DianFa Research Institute of Information Fusion, Naval Aeronautical and Astronautical University, Yantai 264001, China 

出　　处：《Science China(Information Sciences)》2010年第11期2343-2351,共9页中国科学（信息科学）（英文版）

基　　金：supported by the National Natural Science Foundation of China (Grant No. 60802088);the Program for New Century Excellent Talents in University (Grant No. NCET-05-0912);the Scientific Research Foundation of Naval Aeronautical and Astronautical University for Young Scholars (Grant No. HYQN201013)

摘　　要：In the non-Gaussian clutter modeled as independent and identically distributed spherically invariant random vectors, three estimators of sample covariance matrix （SCM）, normalized sample covariance matrix （NSCM） and the corresponding recursive estimator （NSCM-RE） are analyzed. Based on the uniform theorem, three corresponding adaptive normalized matched filters （ANMF） are evaluated from the standpoint of constant false alarm rate （CFAR） property. The theoretical results demonstrate that the SCM-ANMF is only CFAR to the normalized clutter covariance matrix （NCCM）; the NSCM-ANMF is only CFAR to the clutter power level; and the NSCM-RE-ANMF with finite number of iterations is still not CFAR to the NCCM. To ensure CFAR property of ANMF, an adaptive estimator （AE） is devised. Moreover, with AE as the initialization matrix for the iterations, the AE-RE is proposed. With finite number of iterations, the corresponding AE-REANMF guarantees CFAR property to both of the NCCM and the clutter power level. Finally, the performance assessment conducted by Monte Carlo simulation confirms the effectiveness of the proposed detectors.In the non-Gaussian clutter modeled as independent and identically distributed spherically invariant random vectors, three estimators of sample covariance matrix （SCM）, normalized sample covariance matrix （NSCM） and the corresponding recursive estimator （NSCM-RE） are analyzed. Based on the uniform theorem, three corresponding adaptive normalized matched filters （ANMF） are evaluated from the standpoint of constant false alarm rate （CFAR） property. The theoretical results demonstrate that the SCM-ANMF is only CFAR to the normalized clutter covariance matrix （NCCM）; the NSCM-ANMF is only CFAR to the clutter power level; and the NSCM-RE-ANMF with finite number of iterations is still not CFAR to the NCCM. To ensure CFAR property of ANMF, an adaptive estimator （AE） is devised. Moreover, with AE as the initialization matrix for the iterations, the AE-RE is proposed. With finite number of iterations, the corresponding AE-REANMF guarantees CFAR property to both of the NCCM and the clutter power level. Finally, the performance assessment conducted by Monte Carlo simulation confirms the effectiveness of the proposed detectors.

关 键 词：non-Gaussian background covariance matrix estimate normalized matched filter constant false alarm rate recursive estimate 

分 类 号：TN957.51[电子电信—信号与信息处理]