Mixed Far and Near Field Sources Localization Based on Matrix Differencing Under Impulsive Noise Environment

‍ ‍In order to improve the performance of mixed far and near field sources location algorithm based on matrix differencing of the second-order covariance matrix （COV-MD） under impulsive noise environment， two revised algorithm based on matrix differencing of the fractional low-order covariance matrix （FLOC-MD）and compressed transform covariance matrix （CTC-MD） are proposed in this paper. Firstly， the proposed algorithms use one-dimensional MUSIC spectral peak search to obtain the direction of arrival （DOA） of far field source signal. Then the matrix difference algorithm is used to eliminate the far field components and reconstruct the extend near field components. Finally， based on the DOA of near-field source which is estimated by the ESPRIT-like method， the range of near field source is estimated by another one-dimensional MUSIC spectral peak search. Computer simulation results show that the performance of CTC-MD algorithm which is not depend on the prior information of the impulsive noise is better than FLOC-MD algorithm，and the performance of CTC-MD and FLOC-MD algorithm are both better than that of COV-MD algorithm and other mixed far and near field sources location algorithms based on second-order statistics in the case of strong impulsiveness and lower signal-to-noise ratio.