Compressive Direction-of-Arrival Estimation via Regularized Multiple Measurement FOCUSS algorithm

摘要

The recently developed Compressed Sensing (CS) theory has made the super-resolution of spectrum estimation possible. In this paper, we exploit the joint sparsity of received signals to develop a new Compressive Direction-of-Arrival Estimation approach via a new Regularized Multiple Measurment FOCal Underdetermined System Solver (RMM-FOCUSS) Algorithm. It can overcome the resolution limitation of traditional spatial energy spectrum estimation algorithm, such as MUSIC algorithm, and present more accurate estimation of direction of multiple sources when there are a few numbers of antenna units. Some experiments are taken to validate the performance of our proposed method.