Pattern Synthesis of Antenna Array Based on Improved Flower Pollination Algorithm

Abstract

Synthesizing antenna arrays is an important issue in antenna design, which directly determines the performance of the antenna. In this letter, a novel improved flower pollination algorithm (IFPA) is proposed for the synthesis of antenna arrays. To enhance the search ability, the IFPA with Cauchy mutation, Elite strategy, and the dynamic conversion probability is presented. Firstly, Cauchy mutation is applied to the global pollination of the FPA, which increases the diversity of the population. Secondly, elite strategy is used for the local pollination of the FPA, which increases the search range of the optimal individual. Finally, the dynamic switch probability is used to improve the convergence speed of the algorithm. The antenna pattern synthesis is chosen to demonstrate the effectiveness and superiority of IFPA compared with other optimization algorithms. The results show that IFPA achieves the lowest maximum side-lobe level and deepest null depth level than particle swarm optimization (PSO) and FPA.