A DOA Estimation Algorithm from Sparse Representation Perspective for Vehicular Application

In this paper, a recovery algorithm of direction-of-arrival (DOA) Estimation based on weighted 1 l minimization for vehicular applications is proposed. We construct an overcomplete basis based on the largest eigenvector of the covariance matrix, aiming at a sharp spatial spectrum that exhibits the high-precision. The theoretical analysis and simulation results demonstrate that the proposed method has an excellent performance in the aspects of accuracy.