DOA Estimation of Coherent Signals Based on Noise Subspace Reconstruction

Abstract

A two-dimensional coherent signals DOA estimation algorithm is proposed. The proposed algorithm makes full use of the self-covariance and mutual covariance information of the received signals to perform noise subspace reconstruction to eliminate coherence. Then uses reduced dimensional root-finding transforms the two-dimensional polynomial solution into two one-dimensional polynomials, and achieves the automatic matching of azimuth and elevation. The simulation results show that the accuracy of the proposed algorithm is significantly better than others.