A fusion estimation method for covariance matrix structure of clutter

被引：0
|
作者：
Wang Z. [1 ]
Jian T. [1 ]
He Y. [1 ]
机构：
[1] Research Institute of Information Fusion, Naval Aviation University, Yantai
来源：
Kongzhi yu Juece/Control and Decision | 2019年 / 34卷 / 09期
关键词：
Adaptive normalized matched filter; Constant false alarm rate; Constrained normalized Frobenius norm; Covariance matrix estimation; Normalized mean square error; Spherically invariant random vector;
D O I：
10.13195/j.kzyjc.2018.0052
中图分类号：
学科分类号：
摘要：
This paper addresses the problem that the optimal or suboptimal clutter covariance matrix estimation method in the specific clutter background is difficult to adapt to the transitional clutter environment. Firstly, a fusion estimation method for the matrix covariance matrix structure, which covers three existing clutter covariance matrix estimation methods by adjusting the parameter, is proposed, and the adaptive characteristics of the adaptive normalized matched filter corresponding to the proposed method are analyzed and verified by simulation experiments. Then, the empirical formula of the parameter is determined, and it conforms to the numerical results. Finally, the proposed method and the existing methods are compared and analyzed from the aspects of estimation accuracy, constant false alarm rate and detection performance. The results show that the proposed method, which has strong ability to adapt to the temporal and spatial gradients of the clutter, has higher accuracy and better detection performance in the transitional clutter environment. © 2019, Editorial Office of Control and Decision. All right reserved.
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页码：2010 / 2014
页数：4
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