A Modified Chicken Swarm Optimization Algorithm for Synthesizing Linear, Circular and Random Antenna Arrays

Antenna arrays can enhance the directivity and save the transmission power of a communication system. Beam pattern optimization for reducing the maximum sidelobe level (SLL) is a classical electromagnetic problem in antenna arrays. In this paper, a novel improved chicken swarm optimization (ICSO) algorithm is proposed to suppress the maximum SLL of the linear antenna array (LAA), the circular antenna array (CAA) and the random antenna array (RAA). Three improved factors that are the global search, the weighting and the local search factors are introduced into the update method of the roosters, the hens and the chicks of the conventional chicken swarm optimization (CSO), respectively, to achieve better optimization results. Simulations are conducted to verify the performance of the proposed ICSO for suppressing the maximum SLL, and the results show that the proposed ICSO can obtain lower maximum SLL in LAA, CAA and RAA cases compared with several benchmark algorithms. Moreover, the stability of ICSO is evaluated and the results show that it outperforms the other algorithms.