Radiation Pattern Comparison of Circular Antenna Arrays Using GA and PSO

In this paper, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to solve a design challenge for non-uniform CAAs (circular antenna arrays) in a single ring with the best SLL (side lobe level) and improved FNBW (first null beam width) as well. An optimal combination of inter-element spacing and current excitation for CAA that provides an array pattern with the greatest possible reduction in SLL and FNBW is determined using these techniques. It is assumed that a CAA is placed on an X-Y plane. A 16- and 20-element circular array is subjected to PSO and GA. On the basis of various simulation results, the performances of side lobe level and first null beam width have been analyzed as shown in Table 1. In Table 1, the maximum reduced side lobe level and the first null beam width is getting for 16- and 20- elements using PSO as compared to GA. Experimental results also show a significant improvement in SLL and FNBW both as compared to the uniform case for the same problem.