准平稳信号的Khatri-Rao积联合稀疏分解DOA估计方法

摘要

A Khatri-Rao (KR) sparse decomposition algorithm based on KR product with sparse signal representation is proposed in the light of direction of arrival (DOA) estimation of quasi-stationary signals. The received data are processed as the joint-sparse multiple-measurement vectors through KR product, and DOA is estimated 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 decomposition 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.%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.