Efficient Algorithms for Implementing Multistage Wiener Filter in Adaptive Arrays
自适应阵列中多级维纳滤波器的有效实现算法

Based on the analysis of the algorithms for implementing Multistage Wiener Filter (MWF), the MWF implemented by the Correlation Subtraction Algorithm (CSA) is proved to be an Unitary MWF (UMWF). The rank reduction performance of UMWF is superior to the original MWF proposed by Goldstein, Reed, and Scharf. In this paper, the block matrixes in the CSA are modified to reduce the size of the observation data vectors step by step in the forward recursion of MWF. The modified block matrixes can also be used in the CSA architecture. The new implementing algorithm needs a lower computation complexity, while keeping almost the same performance as the CSA. The validity of the proposed algorithm is proved by the simulation results.