基于电磁矢量阵列的加权极化平滑解相干算法

摘要

针对极化平滑(polarization smoothing,PS)算法解相干源时没有利用子阵的互相关信息导致分辨率较差的问题,提出一种新的解相干源预处理方法——加权极化平滑(weighted polarization smoothing,WPS)算法.该算法利用了电磁矢量阵列6个分量组成的子阵的全部自相关和互相关信息.对接收阵列协方差矩阵的36个子矩阵做加权滑动平均,得到等效阵列协方差矩阵,以该协方差矩阵对角化为约束,推导最优加权系数的理论表达式,并分析等效信源协方差矩阵的秩,得到WPS算法最大的解相干源数为6.计算机仿真结果表明WPS算法与PS算法相比具有更高的分辨性能和估计精度.%No utilization of the cross-correlation information among the smoothed subarrays leads to the low resolution of polarization smoothing (PS) algorithms. An improved polarization smoothing algorithm of direction-of-arrival estimation for coherent sources is proposed, which is called the weighted polarization smoothing (WPS) algorithm. Full use of auto-correlation and cross-correlation of the subarrays consisting of six components of electromagnetic vector-sensor array is performed in the WPS algorithm. An equivalent covariance matrix is obtained by a weighted sum of 36 sub-matrixes. The derivation of theoretical formula of optimal weighting coefficients and an analysis of the rank of the equivalent signal covariance matrix constrained by its diagonalization are accomplished. Simulation results show that the WPS algorithm has higher resolution and accuracy compared with the PS one.