基于Bayes准则的STAP协方差矩阵估计算法

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Covariance matrix estimation for the STAP based on the Bayes criterion

LIU Cong-feng;LIAO Gui-sheng

(Key Lab. of Radar Signal Processing, Xidian Univ., Xi′an 710071， China)

Received:1900-01-01 Revised:1900-01-01 Online:2008-04-20 Published:2008-03-28
Contact: LIU Cong-feng E-mail:cfliu@mail.xidian.edu.cn

Abstract

Abstract: For the environment in which the clutter power changes slowly with distance, a novel weighting maximum likelihood estimation (WMLE) algorithm is proposed that uses the Bayes criterion to improve the approximative covariance matrix estimation for Space-Time Adaptive Processing (STAP). By the event definition and the Bayes criterion, the precise computing method for the weight coefficient is given, this method also gives the efficient solution to finding the weight coefficient for WMLE. Simulation attests its correctness and effectiveness.

Key words: Space-time adaptive processing, nonhomogeneous condition, covariance matrix estimation, data weighting, Bayes criterion

CLC Number:

TN911

LIU Cong-feng;LIAO Gui-sheng. Covariance matrix estimation for the STAP based on the Bayes criterion
[J].J4, 2008, 35(2): 223-227.

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Covariance matrix estimation for the STAP based on the Bayes criterion

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