电磁矢量阵中基于平行因子压缩感知的角度估计算法  

Angle Estimation for Electromagnetic Vector Sensor Array via Compressed Sensing-Parallel Factor

作　　者：张小飞[1] 李书[1] 郑旺[1] 

机构地区：[1]南京航空航天大学电子信息工程学院,南京211106

出　　处：《数据采集与处理》2016年第2期268-275,共8页Journal of Data Acquisition and Processing

基　　金：国家自然科学基金(61371169)资助项目

摘　　要：将平行因子框架与压缩感知理论相结合,解决了电磁矢量传感器阵列中的波达方向估计问题。首先将接收信号构建成平行因子模型,然后结合压缩感知理论,对平行因子模型压缩。根据三线性交替最小二乘算法对压缩后的平行因子模型进行分解,最后利用信号的稀疏性,得到波达方向估计。借助压缩过程,本文算法降低了传统的平行因子算法的计算复杂度,节约了存储空间。本文算法无需谱峰搜索,且同时适用于均匀线阵和非均匀线阵。该算法的角度估计性优于ESPRIT算法,且接近传统的基于平行因子模型的角度估计算法,仿真结果证明该算法的有效性。We combine the parallel factor framework with the compressed sensing theory to solve the problem of the direction of arrival estimation for the electromagnetic vector sensor array .We first rear‐range the received data matrix as a parallel factor model ,and compress it to a smaller one based on the compressed sensing theory .Then the trilinear alternating least square algorithm is exploited to decom‐pose the compressed parallel factor model .Finally ,the angle estimation is obtained with sparsity .Owing to compression ,the computational complexity of the algorithm is lower than that of the conventional par‐allel factor model‐based algorithm ,and more storage memory is saved .The algorithm needs no peak searching and is applicable to both uniform and non‐uniform linear array .Moreover ,the angle estimation performance of the proposed algorithm is better than that of the ESPRIT algorithm and close to that of the conventional parallel factor model‐based algorithm ,which can be verified by various simulations .

关 键 词：平行因子 压缩感知 波达方向估计 电磁矢量传感器 

分 类 号：TN911.7[电子电信—通信与信息系统]