改进的多目标粒子群算法综合激励受限的共形阵
收稿日期: 2012-10-11
修回日期: 2013-01-21
网络出版日期: 2013-03-27
Improved Multi-objective Particle Swarm Optimization Algorithm for Synthesizing Conformal Arrays with Excitations Restricted
Received date: 2012-10-11
Revised date: 2013-01-21
Online published: 2013-03-27
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。
赵菲 , 柴舜连 , 叶良丰 , 齐会颖 , 毛钧杰 . 改进的多目标粒子群算法综合激励受限的共形阵[J]. 航空学报, 2013 , 34(8) : 1944 -1952 . DOI: 10.7527/S1000-6893.2013.0117
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.
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