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

作　　者：YANG XiaoPeng LIU YongXu LONG Teng 

机构地区：[1]School of Information and Electronics,Beijing Institute of Technology

出　　处：《Science China(Information Sciences)》2013年第4期119-130,共12页中国科学（信息科学）（英文版）

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

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 directly. According 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 significantly. The proposed method requires initially calculating the inverse covariance matrix of the first pulse-order recursively based on the block Hermitian matrix property. In the fol- lowing, the inversion of space-time covariance matrix is obtained recursively based on the previous pulse-order inverse covariance matrix. Next, the STAP adaptive weight is calculated based on the inversion space-time covariance matrix previously obtained. Compared 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 performance. This method can be applied to practical systems benefiting from small computational complexity and stable clutter suppression performance.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 directly. According 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 significantly. The proposed method requires initially calculating the inverse covariance matrix of the first pulse-order recursively based on the block Hermitian matrix property. In the fol- lowing, the inversion of space-time covariance matrix is obtained recursively based on the previous pulse-order inverse covariance matrix. Next, the STAP adaptive weight is calculated based on the inversion space-time covariance matrix previously obtained. Compared 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 performance. This method can be applied to practical systems benefiting from small computational complexity and stable clutter suppression performance.

关 键 词：space-time adaptive processing recursive method computational complexity clutter suppression inverse covariancematrix 

分 类 号：TN957.51[电子电信—信号与信息处理] O212.1[电子电信—信息与通信工程]