Planar array design based on the GEBPSO-vm algorithm

In this paper, we propose a modified Boolean Particle Swarm Optimization velocity mutual (GEBPSO-vm) algorithm to design thinned planar array, and then optimize the side lobe level of thinned planar array. This new algorithm introduces the concept of feedback factor and G inertia weight factor. The feedback factor will generate an additional speed factor, which makes the evolution direction of the population have adaptive regulation function. The G inertia weight factor allows each particle swarm has a unique local adaptive weight. It is shown that the side lobe level, the sparsity and convergent speed of the planar array are improved by GEBPSO-vm. The simulation results of side lobe level, the sparsity and convergent speed are presented.