A Novel Binary Butterfly Mating Optimization Algorithm with Subarray Strategy for Thinning of Large Antenna Array

This paper presents a novel binary algorithm named as binary butterfly mating algorithm (BBMO) combined with subarray strategy for thinning of antenna array. The proposed algorithm has been adapted from a recently developed nature inspired optimization, butterfly mating optimization (BMO). The subarray strategy is dividing the linear array into two parts, one part with a fixed number of element turned on in the middle of array and the rest elements on the edge of array composing another subarray. In order to reduce the complexity of the thinning process, BBMO algorithm is used to optimize the element on the edge of an array. The proposed BBMO with subarray strategy is used to synthesize a linear sparse antenna array in order to reduce maximum sidelobe level and at the same time keeping the percentage of thinning equal to or more than the desired level. To evaluate the performance of the proposed thinning method, a linear array with 100 elements is optimized by BBMO algorithm without and with subarray strategy. And we discuss the impact of number of fixed elements on thinning results. The novel method BBMO with subarray strategy gives reduced SLL as compared to the results available in literature of ant colony algorithm, genetic algorithm, binary differential evolution algorithm, chaotic binary particle swarm optimization, and improved binary invasive weed optimization algorithm. Moreover, the convergence rate of BBMO with subarray strategy is faster than BBMO without subarray strategy and the other methods.