Pattern Synthesis of 2-D Arrays Based on a Modified Particle Swarm Optimization Algorithm
基于改进的粒子群算法的二维阵列天线方向图综合技术

A modified Particle Swarm Optimization (PSO) algorithm is proposed and used to optimize the sidelobe level of plane arrays, in which special techniques as global best perturbation and jumped inertia weight strategy are adopted. The PSO algorithm is also used to select a better combination of optimal parameters for itself. So that the convergent speed and accuracy of the algorithm are improved. The simulation results of sidelobe reduction of 2-D arrays and pattern synthesis of a sparse array show that it is effective.