航空学报 > 2013, Vol. 34 Issue (8): 1944-1952   doi: 10.7527/S1000-6893.2013.0117

改进的多目标粒子群算法综合激励受限的共形阵

赵菲1,2, 柴舜连2, 叶良丰2, 齐会颖2, 毛钧杰2   

  1. 1. 中国西南电子电信技术研究所, 四川 成都 610041;
    2. 国防科学技术大学 电子科学与工程学院, 湖南 长沙 410073
  • 收稿日期:2012-10-11 修回日期:2013-01-21 出版日期:2013-08-25 发布日期:2013-03-27
  • 通讯作者: 赵菲 E-mail:bitzhaofei@163.com
  • 作者简介:赵菲 男,博士,助理研究员。主要研究方向:共形天线阵列理论与设计。Tel:0731-84573440 E-mail:bitzhaofei@163.com;柴舜连 男,博士,教授,博士生导师。主要研究方向:新型天线理论与工程。Tel:0731-84573440 E-mail:slchai@sina.com;叶良丰 男,博士研究生。主要研究方向:电磁场数值算法。Tel:0731-84573440 E-mail:yeliangfeng2010@hotmail.com

Improved Multi-objective Particle Swarm Optimization Algorithm for Synthesizing Conformal Arrays with Excitations Restricted

ZHAO Fei1,2, CHAI Shunlian2, YE Liangfeng2, QI Huiying2, MAO Junjie2   

  1. 1. Southwest Electronics and Telecommunication Technology Research Institute, Chengdu 610041, China;
    2. College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China
  • Received:2012-10-11 Revised:2013-01-21 Online:2013-08-25 Published:2013-03-27

摘要:

针对激励限制下的共形阵功率方向图综合问题,提出一种改进的多目标粒子群优化(IMOPSO)算法。将共形阵列在激励限制条件下的综合命题,转化为激励优化和功率方向图赋形的多目标优化命题。IMOPSO算法通过引入多子群寻优、粒子聚焦距离优选、非支配解集修剪以及新生粒子微扰复制等机制,显著提高了传统多目标粒子群优化(MOPSO)算法所构建Pareto解集的优越性和散布性。IMOPSO算法成功用于12元微带柱面共形阵非赤道面的方向图综合,获得了不同约束条件下最优余割平方波束方向图综合结果集合,综合过程考虑了各阵元的互耦作用,为规划共形相控阵的激励限制提供了极有价值的参考。

关键词: 共形天线阵, 多目标粒子群优化, 方向图综合, 激励限制, 互耦

Abstract:

For the purpose of power pattern synthesis for conformal arrays with excitations restricted, an improved multi-objective particle swarm optimization (IMOPSO) algorithm is proposed. By applying this IMOPSO algorithm, the original problem can be transformed into a multi-objective optimization problem in which excitation optimization and power pattern synthesis are considered at the same time. By introducing multi-subgroup optimization, particle focused distance selection, Pareto solution set cutting, and a new particle copy mechanism, the performance of the IMOPSO algorithm is improved significantly as compared with the traditional multi-objective particle swarm optimization (MOPSO) algorithm. Moreover, IMOPSO algorithm is applied to synthesizing multiple-pattern in 12-element microstrip cyclinder sector conformal array in non-equatorial plane successfully, and a set of power patterns with different excitation restrictions for microstrip conformal arrays is achieved by IMOPSO algorithm, with the mutual coupling and polarizing deterioration of the elements considered. This offers a valuable reference for designing feed strategies of conformal phased array conformal phased array.

Key words: conformal antenna array, multi-objective particle swarm optimization, pattern synthesis, excitation restricted, mutual coupling

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