Adaptive Dynamic Meta Particle Swarm Optimization Algorithm Synthesizing Multiple-pattern Conformal Array

Based on the general element active pattern achieved by full wave simulation, a novel Adaptive Dynamic Meta Particle Swarm Optimization (ADMPSO) algorithm is proposed for synthesizing multiple-pattern conformal array. The dominated subgroup and nondominated subgroup are defined on the basis of traditional Meta particle swarm. Meanwhile, the adaptive dynamic modulating for multiple-subgroup is realized by introducing the downsizing of nondominated subgroup, the dominated subgroup expansion, and the updating for the adaptive inertia weights, which improve the optimization performance of ADMPSO. Furthermore, ADMPSO algorithm is applied to synthesizing multiple-pattern in 12-element microstrip conic sector conformal array in non-equatorial plane successfully, with the polarizing deterioration of the element considered. And the pencil beam, the flat-top beam, and the cosecant squared beam patterns are achieved simultaneously, with the common amplitude of the excitation restricted. The simulation shows that the optimization results and convergent speed are significantly improved compared with other algorithms.