Pulse-order recursive method for inverse covariance matrix computation applied to space-time adaptive processing

作     者：YANG XiaoPeng LIU YongXu LONG Teng 

作者机构：School of Information and ElectronicsBeijing Institute of Technology 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2013年第56卷第4期

页      面：123-134页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 02[经济学] 0809[工学-电子科学与技术（可授工学、理学学位）] 07[理学] 08[工学] 070103[理学-概率论与数理统计] 0810[工学-信息与通信工程] 0202[经济学-应用经济学] 020208[经济学-统计学] 081105[工学-导航、制导与控制] 081001[工学-通信与信息系统] 0714[理学-统计学（可授理学、经济学学位）] 081002[工学-信号与信息处理] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 0701[理学-数学] 

基　　金：supported in part by National Nature Science Foundation of China (Grant Nos. 61001198 61032009 61225005) 

主　　题：space-time adaptive processing recursive method computational complexity clutter suppression inverse covariance matrix 

摘      要：The conventional space-time adaptive processing(STAP) method such as the typical sample matrix inversion(SMI)-based STAP method is difficult to implement for a practical system because intense computational complexity arises in calculating the inversion of a space-time covariance matrix *** to the block Hermitian matrix property of space-time covariance matrix,a new pulse-order recursive method is proposed in this paper to calculate the inverse covariance matrix for the STAP adaptive weight,which can reduce the computational complexity *** proposed method requires initially calculating the inverse covariance matrix of the first pulse-order recursively based on the block Hermitian matrix *** the following,the inversion of space-time covariance matrix is obtained recursively based on the previous pulse-order inverse covariance ***,the STAP adaptive weight is calculated based on the inversion space-time covariance matrix previously *** with the conventional SMI-based STAP algorithms,the computational complexity of the proposed method is reduced to more than 50% for the same clutter suppression *** method can be applied to practical systems benefiting from small computational complexity and stable clutter suppression performance.