多种群首领决策遗传算法优化阵列天线

Multi-population leader dominating genetic algorithm optimizing antenna arrays

针对简单遗传算法(Simple Genetic Algorithm,SGA)的不足,提出多种群首领决策遗传算法(Multi-Population Leader Dominating Genetic Algorithm,MPLDGA).通过将普通个体和首领进行交叉、多种群进化等策略,使得MPLDGA具有收敛速度快、全局搜索能力强、消耗时间短等优点.利用该算法,首先优化设计了18元线阵的激励系数,实现了覆盖-5°~25°的余割平方方向图,副瓣电平优于-30dB.最后,优化设计了具有401个单元的平面稀疏阵列,实现了在稀疏率为60.8%时副瓣电平优于-21.9dB.

Multi-population leader dominating genetic algorithm (MPLDGA) is presented to overcome the shortcomings of the simple genetic algorithm (SGA). In the MPLDGA, the common individuals are crossed with the leader and the muti-population evolution strategy is adopoted, which make the MPLDGA with merits of fast convergence rate, robust global searching ability and less time-cost. Firstly, the algorithm is adopoted to optimize the excitation cooefficients of a 18-element linear array, and a cosecant-squared pattern ranging from-5° to 25° is realized with the side-lobe levels better than -30 dB. Finally, it is adopoted to optimize a 401-element planar sparse array, and the side-lobe levels are better than -21.9 dB at a thinning percentage of 60.8%. Copyright © 2015 by Editorial Department of Chinese Journal of Radio Science