Direction Finding of Maximum Likelihood Algorithm Using Artificial Bee Colony in the Impulsive Noise

A virtual multi-element uniform linear array is constructed through fractional lower order covariance matrix of the minimum redundant array in the presence of impulsive noise. Based on virtual multi-element uniform linear array and reconstructed fractional lower order covariance matrix, a novel maximum likelihood (ML) algorithm is proposed. The proposed algorithm utilized few virtual elements and expanded the number of effective aperture array, while significantly improving the performance of the original ML algorithms. In order to fit the proposed direction finding algorithm based on the minimum redundant array and fractional lower order covariance matrix, a bee colony algorithm is applied to objective function of direction finding. Monte-Carlo simulations have proved that the proposed method has some good performance such as high resolution in the presence of impulse noise and the capability of using a small number of elements to find more signal sources.