一种基于KL分离度的改进矩阵CFAR检测方法

doi:10.11999/JEIT150711

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Abstract

The matrix CFAR detector is proposed according to information geometry theory, but its constant false alarm property is not analysed, and the matrix CFAR’s detection performance still needs to be improved. Firstly, the matrix CFAR’s constant false alarm property is analysed according to the normal law on matrix manifold, on this basis an improved matrix CFAR detector is proposed with replacing the geodesic distance with KULLBACK-LEIBLER Divergence (KLD). Finally, simulation experiments verify that the improved method has better detection performance.

Key words： Information geometry Constant False Alarm Rate (CFAR) detection Statistic manifold Geodesic distance KULLBACK-LEIBLER Divergence (KLD) (relative entropy)

Received: 10 June 2015 Published: 03 February 2016

PACS:

TN957.51

Fund:

The National Natural Science Foundation of China (61179014), Youth Science Fund Project (61302193)

Corresponding Authors: ZHAO Xinggang E-mail: 565484636@qq.com

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	ZHAO Xinggang
	WANG Shouyong

Cite this article:

ZHAO Xinggang,WANG Shouyong. An Improved Matrix CFAR Detection Method Base on KL Divergence[J]. JEIT, 2016, 38(4): 934-940.

URL:

http://jeit.ie.ac.cn/EN/10.11999/JEIT150711 OR http://jeit.ie.ac.cn/EN/Y2016/V38/I4/934

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