An Intelligent Multiple Moving Targets Tracking Method in the Presence of Impulsive Noise

In order to obtain the directions for multiple moving targets under impulsive noise environment, a novel maximum likelihood (ML) algorithm based on quantum cultural geese swarm algorithm (QCGSA) is proposed. The method first sets a special array structure of nonuniform linear array, and then locates the targets in a changing search range, and then designs QCGSA to resolve ML function. Utilizing the QCGSA’s search mechanism, the method finally searches for the optimal angle value for maximum likelihood equation of extended weighted signals in the search space. Through decreasing search range gradually and utilizing intelligent search mechanism, the proposed method improves the searching time. Simulation results demonstrate that the proposed tracking method for multiple moving targets under impulsive noise environment can guarantee the real time property and has the ability of both array extension and good performance under impulsive noise environment. Keywords—fractional lower order covariance; maximum likelihood algorithm; minimum redundancy linear array; quantum cultural geese swarm; impulsive noise;