Realizing stepped amplitude quantization of low sidelobe linear array using particle swarm optimization algorithm

Two approaches towards realizing stepped amplitude quantization of low sidelobe linear array based on particle swarm optimization (PSO) are presented. One approach is series-PSO algorithm consisting of constrained PSO algorithm coping with integer variables, corresponding with step widths, and PSO algorithm for quantized amplitude weights. The other method is PSO algorithm with the penalty function method using random approximation strategy for integer variables. Method two is better than method one in term of peak sidelobe level (PSLL) and half-power beam width (HP), but method one is more robust than method two. Simulation experiment shows the efficiency of two methods.