High-resolution DOA estimation based on independent noise component for correlated signal sources

Abstract

In this article, a modified complex-valued FastICA algorithm is utilized to extract the specific feature of the Gaussian noise component from mixtures so that the estimated component is as independent as possible to the other non-Gaussian signal components. Once the noise basis vector is obtained, we can estimate direction of arrival by searching the array manifold for direction vectors, which are as orthogonal as possible to the estimated noise basis vector especially for highly correlated signals with closely spaced direction. Superior resolution capabilities achieved with the proposed method in comparison with the conventional multiple signal classification (MUSIC) method, the spatial smoothing MUSIC method, and the signal subspace scaled MUSIC method are shown by simulation results.