Robust Coherent sources Localization Based on Hankel Matrix Reconstruction

The performance of the subspace-based direction of arrival (DOA) estimation degrades in coherent source scenarios due to rank deficiency of the covariance matrix of array-received signals. To solve this problem, various methods such as the spatial smoothing preprocessing (SSP) and covariance matrix reconstruction methods have been proposed. However, these methods do not make fully use of the available information in the covariance matrix and their performance deteriorates under low signal-to-noise ratio (SNR) conditions. In this paper, we propose a DOA estimation method for coherent sources which is robust to low SNR. Specifically, a Hankel matrix is constructed by the elements in the rank-1 signal subspace of the covariance matrix of the denoised array-received signals, in order to recover a rank-k signal subspace. Then, the MUSIC method is used with the noise subspace of this Hankel matrix for coherent source localization. The simulation results show that the proposed algorithm can make full use of the available information in the covariance matrix of array-received signals and effectively estimate the DOA of coherent sources under low SNR conditions.