Abstract:

To solve the problem of DOA estimation for coherent signals in the presence of spatial correlated noises, an algorithm, called the DLISDS (diagonal loadingimproved spatial smoothing difference), is proposed. By exploiting the property of Teoplitz decomposition of the covariance matrix, the DLISDS method can eliminate correlated noises and resolve the uncorrelated and coherent signal separately. In this way the output data of the array are used repeatedly, and more sources can be estimated. Compared with the conventional methods, the DLISDS can resolve more sources using the same number of sensors. In addition, the algorithm could skip sources number estimation and EVD (eigenvalue decomposed), so it has smaller computational complexity. The computer’s simulation results verify the correctness and effectiveness of the proposed DLISDS method.