Reduction of Dynamic Range Ratio through Competition Over Resources to synthesize planar array antennas

Abstract

To synthesize planar arrays, a new optimization algorithm namely Competition Over Resources (COR) is presented. This method imposes deeper nulls with the constraint of Side Lobe Level (SLL). COR is a new meta-heuristic algorithm based on competitive behavior of animal groups over food resources. The algorithm restricts Dynamic Range Ratio (DRR) in order to achieve a better control of the mutual coupling and feed network. Simulation results for optimal patterns, possessing multiple and broad nulls, are presented. The approach is implemented based on the position-only and the space/amplitude optimization. Furthermore, in order to find the better performance in imposing deeper nulls and reducing SLL, a comparative evaluation between Particle Swarm Optimization (PSO) and COR is presented. Numerical results show that COR has better performance compared with PSO.