摘要
对加权空间平滑算法计算加权因子时需要预估计信源方向的问题,提出了一种新的相干信源波达方向估计的加权空间平滑算法。在计算加权矩阵时不需要知道信源的先验信息,也不需要预估计信源方向,而是对原始阵列进行特殊结构的子阵划分,结合子阵间的自、互相关矩阵对角度估计的贡献不同,采用嵌套的空间平滑算法得到加权矩阵,从而实现相干信源的解相干和波达方向估计。本文算法相比原算法具有更优的加权因子、更好的解相干性能、更高的角度分辨率和角度估计的准确性。理论分析和仿真结果表明新算法的有效性。
The weighted spatial smoothing（WSS）algorithm requires preliminary estimate direction-of-arrival of coherent signals in the calculation of weight factors.Here a new improved weighted spatial smoothing（IWSS）technique for the direction-of-arrival estimation of coherent signals is proposed.It divides the array into several sub-arrays with special structure,according to the different contribution to direction-of-arrival estimation between the autocorrelation matrix and the cross correlation matrix.Nested spatial smoothing algorithm is applied to gain the weight matrix to decorrelate and estimate the directionof-arrival of coherent source signals.In contrast to the WSS method,the higher decorrelation performance and angel resolution are also obtained without a priori information and preliminary estimate angle value.Theoretical analysis and simulation results demonstrate the correctness and validity of the new algorithm.
出处
《数据采集与处理》
CSCD
北大核心
2015年第4期824-829,共6页
Journal of Data Acquisition and Processing
基金
陕西省自然科学基金(2011JQ8041)资助项目
中央高校基本科研业务费专项基金(2013G1241116)资助项目
关键词
波达方向估计
互相关矩阵
加权空间平滑
direction-of-arrival estimation
cross correlation matrix
weighted spatial smoothing
