A new optimizing method for planar arrays pattern

Abstract

Traditional particle swarm optimization(PSO) will be failed because of falling into local optimum solutions and converging too slowly when being used to optimize planar array pattern. So a new method is presented to improve the traditional PSO convergence by means of efficient estimation of the optimum particle's initial values. A desired pattern is first constructed, and then the corresponding aperture weights can be estimated by means of matrix operation. These weights then are assigned to a particle as initial values(this operation is equivalent to making an efficient estimation of the optimum particle's initial values), while the other particles are initialized randomly, then the traditional PSO algorithm is used to search for the global best solutions. The simulation results proved that this method could rapidly converge to satisfying global solutions and the desired aperture weights could be achieved. So this improved PSO method presented here is far better than the traditional PSO to solve the optimization problems of planar array pattern.