An Improved Matrix CFAR Detection Method Base on KL Divergence

ZHAO Xinggang; WANG Shouyong

doi:10.11999/JEIT150711

Volume 38 Issue 4

Apr. 2016

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ZHAO Xinggang, WANG Shouyong. An Improved Matrix CFAR Detection Method Base on KL Divergence[J]. Journal of Electronics & Information Technology, 2016, 38(4): 934-940. doi: 10.11999/JEIT150711

Citation:

ZHAO Xinggang, WANG Shouyong. An Improved Matrix CFAR Detection Method Base on KL Divergence[J]. Journal of Electronics & Information Technology, 2016, 38(4): 934-940. doi: 10.11999/JEIT150711

ZHAO Xinggang, WANG Shouyong. An Improved Matrix CFAR Detection Method Base on KL Divergence[J]. Journal of Electronics & Information Technology, 2016, 38(4): 934-940. doi: 10.11999/JEIT150711

Citation:

ZHAO Xinggang, WANG Shouyong. An Improved Matrix CFAR Detection Method Base on KL Divergence[J]. Journal of Electronics & Information Technology, 2016, 38(4): 934-940. doi: 10.11999/JEIT150711

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An Improved Matrix CFAR Detection Method Base on KL Divergence

doi: 10.11999/JEIT150711

ZHAO Xinggang¹,
WANG Shouyong¹

Funds:

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

Received Date: 2015-06-10
Rev Recd Date: 2015-12-18
Publish Date: 2016-04-19

Abstract

Abstract

The matrix CFAR detector is proposed according to information geometry theory, but its constant false alarm property is not analysed, and the matrix CFARs detection performance still needs to be improved. Firstly, the matrix CFARs 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.

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References(20)

References

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