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1. (WO2018045567) ROBUST STAP METHOD BASED ON ARRAY MANIFOLD PRIORI KNOWLEDGE HAVING MEASUREMENT ERROR

Pub. No.:    WO/2018/045567    International Application No.:    PCT/CN2016/098599
Publication Date: Fri Mar 16 00:59:59 CET 2018 International Filing Date: Sat Sep 10 01:59:59 CEST 2016
IPC: G01S 7/41
Applicants: SHENZHEN UNIVERSITY
深圳大学
Inventors: YANG, Zhaocheng
阳召成
QUAN, Guihua
全桂华
HUANG, Jianjun
黄建军
HUANG, Jingxiong
黄敬雄
Title: ROBUST STAP METHOD BASED ON ARRAY MANIFOLD PRIORI KNOWLEDGE HAVING MEASUREMENT ERROR
Abstract:
A robust STAP method based on array manifold priori knowledge having measurement error comprises the steps of: S1, obtaining a clutter space-time steering vector set according to a given error range; S2, searching for an important space-time steering vector in the clutter space-time steering vector set, and calculating an eigenvalue and an eigenvector of the important space-time steering vector; and S3, obtaining a clutter covariance matrix according to the eigenvalue and the eigenvector of the important space-time steering vector, and obtaining a filter weight vector according to the clutter covariance matrix. Errors unavoidably exist in obtaining array manifold knowledge, which directly causes processing performance limitation of STAP based on the array manifold knowledge. Compared with the STAP method based on array manifold knowledge in the prior art, the method reduces requirements for the accuracy of priori knowledge, has a robust characteristic for the priori knowledge having certain errors, and can avoid a process of clutter covariance matrix inversion in designing a filter, thereby achieving the objective of reducing the computation complexity of a system.