准平稳信号的Khatri-Rao积联合稀疏分解DOA估计方法  

DOA estimation of quasi-stationary signals based on Khatri-Rao product using joint sparse signal representation

作　　者：刘庆华[1] 欧阳缮[1,2] 何振清[2] 

机构地区：[1]西安电子科技大学电子工程学院,陕西西安710071 [2]桂林电子科技大学信息与通信学院,广西桂林541004

出　　处：《系统工程与电子技术》2012年第9期1753-1757,共5页Systems Engineering and Electronics

基　　金：国家自然科学基金(60972084;61062003;61162007);国家重点基础研究发展计划(973计划)(2008CB317109);广西自然科学基金(0832007Z);广西无线宽带通信与信号处理重点实验室2011年度主任基金(11104;11106)资助课题

摘　　要：针对准平稳信号的波达方向估计,提出一种基于Khatri-Rao(KR)积的联合稀疏分解算法。该算法借助KR积将阵列接收数据表示成多个虚拟联合稀疏测量矢量模型,通过求解联合稀疏反问题实现波达方向估计,给出了联合稀疏反问题的唯一性条件,解决了当前稀疏分解方位估计不能处理欠定情况的问题。仿真实验验证了算法的有效性,在低信噪比下获得了更高的分辨率。A Khatri-Rao （KR） sparse decomposition algorithm based on KR product with sparse signal rep- resentation is proposed in the light of direction of arrival （DOA） estimation of quasi-stationary signals. The re- ceived data are processed as the joint-sparse multiple-measurement vectors through KR product, and DOA is es- timated by solving the joint-sparse inverse problem. The existence and uniqueness condition of the joint-sparse inverse problem is also provided, which addresses the issue that the present DOA estimation with sparse decom- position can not handle the underdetermined situation. The simulation results demonstrate the effectiveness of the proposed approach and the higher resolution in a lower signal-to-noise ratio environment.

关 键 词：波达方向估计 稀疏分解 反问题 准平稳信号 Khatri—Rao积 

分 类 号：TN911.7[电子电信—通信与信息系统]