一种新型混合优化算法及其在星载多波束天线赋形中的应用  

A Novel Hybrid Optimization Algorithm and Its Application in Pattern Synthesis for a Multiple-Beam Satellite Antenna

作　　者：李章义 万国宾[1] 张静[1] 

机构地区：[1]西北工业大学电子信息学院,西安710129

出　　处：《现代应用物理》2014年第4期322-327,共6页Modern Applied Physics

基　　金：西北工业大学研究生创业种子基金(Z2014014)

摘　　要：基于萤火虫算法(FA)全局搜索能力强、粒子群优化算法(PSO)局部优化效果出色的特点,提出一种新型混合优化算法,FAPSO,它融合了PSO和FA的迭代机制,增加了群体多样性。仿真结果表明:FAPSO的全局极值逼近精度、收敛速度及算法鲁棒性远好于PSO、FA和实数遗传算法(GA);将FAPSO和PSO用来优化星载多波束抛物面天线的赋形波束,对比验证了FAPSO的良好性能,为波束赋形设计问题提供了新的思路。A novel hybrid optimization algorithm, FAPSO, is proposed based on firefly algorithm（FA） and particle swarm optimization algorithm（PSO）. FAPSO combines PSO＇s and FA＇s iteration theories, and increases the population diversity. Simulation tests show that FAPSO has the highest convergence rate, the best exactness and robustness compared to PSO, FA, and real genetic algorithm（GA）. Finally, FAPSO is applied to the pattern synthesis for a multiple-beam satellite antenna, and the simulation results reveal that FAPSO is reasonable and effective. Thus, FAPSO provides a new idea to deal with beam-shaping problems.

关 键 词：混合优化算法 萤火虫算法 粒子群优化算法 多波束天线 赋形 

分 类 号：O242.28[理学—计算数学] TN820.1[理学—数学]