An effective DOA estimation method of coherent signals based on reconstruct weighted noise subspace

Abstract

For the problem that traditional DOA (Direction Of Arrival) estimation algorithms often fail to deal with coherent signals, a new high accuracy DOA estimation method based on weighted noise subspace is proposed. Considering the received data matrix obtained by uniform liner array, the proposed method makes full use of the cross-covariance information of it to construct an augmented matrix and performs singular value decomposition on it. In order to obtain more accurate signal vectors, a new weighted noise subspace is reconstructed, and the weighted factor matrix is designed to maintain the consistency of eigenvectors. Finally, combined the new noise subspace and weighted factor matrix completes the DOA estimation of coherent signals. Simulation results are presented to demonstrate the effectiveness of the proposed method, especially in low signal-to-noise ratio (SNR) and small number of snapshots. And without losing the aperture of array, the new method can estimate the DOA of coherent signals successfully.