High resolution bearing estimations by covariance matrix approximation

An iterative high resolution bearing estimation algorithm is presented in the paper. This algorithm approximates the signal component of the covariance matrix in the least square error sense such that the approximated matrix conforms with a known structure. Here the number of the sources is assumed to be known a priori. The obtained matrix has a rank equal to the number of sources and consists of the products of the estimated signal source phase vectors. This algorithm requires only one dimensional search and can be applied to nonuniformly spaced arrays. Computer simulation results show that the algorithm has significant improvement compared to MUSIC method when the number of samples is small and SNR is low.