Optimization of Concentric Circular Arrays Using a Crossover Improved Genetic Algorithm

Abstract

Concentric circular antenna array is one of the widely used antenna array configuration in the field of communications due to its capability to scan an all-azimuth and has a beam pattern which is invariant in nature. This paper presents a technique for optimizing the excitation amplitudes of a concentric circular array. The well-known soft computing technique, the Genetic Algorithm (GA) having an improved crossover has been employed to minimize the side lobes levels. The crossover improved GA (CIGA) echoes the motion of fireflies used in the Firefly Algorithm (FA). Simulation results obtained will ensure the productiveness of the proposed method.