基于加权1范数稀疏信号重建的DoA估计  

Do A Estimation Based on Sparse Signal Recovery Utilizing Weighted 1 Norm

作　　者：赵季红[1,2] 马兆恬 曲桦[2] 王伟华[2] 李雷雷[1] ZHAO Jl-hong MA Zhao-tian QU Hua WANG Wei-hua LI Lei-lei(School of Communication and Information Engineering, Xi＇an University of Posts and Telecommunications, Xi＇an 710121, China The School of Electronic and Information Engineering, Xi＇an Jiaotong University, Xi＇an 710054, China)

机构地区：[1]西安邮电大学通信与信息工程学院,西安710121 [2]西安交通大学电子与信息工程学院,西安710054

出　　处：《北京邮电大学学报》2016年第5期33-36,66,共5页Journal of Beijing University of Posts and Telecommunications

基　　金：国家自然科学基金项目(61372092)

摘　　要：针对l1范数下奇异值分解的l1-SVD稀疏信号重建的波达方向估计方法存在求解量的稀疏性较差且空间谱中存在较多的伪峰,不能准确估计波达方向的问题,对接收信号矩阵进行预处理,并使用信号子空间设计权值矢量得到更好的稀疏性和更好地逼近l0范数,利用得到的权值矢量对l1-SVD算法中解矢量的各个元素进行加权,以得到的加权l1范数作为最小化的目标函数进行优化.仿真结果表明,提出的算法在快拍数、正则化参数和信噪比等条件改变的情况下能有效抑制伪峰,并准确稳定地估计出波达方向.When l1-SVD algorithm is used for direction of arrival（ Do A） estimation with few snapshots and low signal noise ratio（ SNR）,there appear pseudo peaks in spatial spectrum,which lead to inaccurately Do A estimation results. To deal with this problem,the article proposes a Do A estimation method based on sparse signal recovery utilizing weighted 1 norm. Based on the sparse recovery,the weight vector is chosen from the signal subspace and received signal matrix is multiplied. Then the product between weights and elements in the result is made to get weighted 1 norm is taken as target function for minimization. Simulations demonstrate that the proposed algorithm could effectively restrain the pseudo peak and accurately estimate the Do A under the different snapshots,regularization parameter and SNR.

关 键 词：波达方向估计 矩阵预处理 稀疏重构 凸优化 

分 类 号：TN929.53[电子电信—通信与信息系统]