J4 ›› 2011, Vol. 38 ›› Issue (3): 175-180.doi: 10.3969/j.issn.1001-2400.2011.03.029

• 研究论文 • 上一篇    下一篇

粒子群算法在阵列天线方向图综合中的应用

王维博1,2;冯全源1
  

  1. (1. 西南交通大学 信息科学与技术学院,四川 成都  610031;
    2. 西华大学 电气信息学院,四川 成都  610039)
  • 收稿日期:2010-06-29 出版日期:2011-06-20 发布日期:2011-07-14
  • 通讯作者: 王维博
  • 作者简介:王维博(1977-),男,讲师,西南交通大学博士研究生,E-mail: okwwb@163.com.
  • 基金资助:

    国家自然科学基金重大项目资助项目(60990320,60990323);国家“863”计划资助项目(2009AA01Z230)

Application of PSO algorithm in pattern synthesis for antenna arrays

WANG Weibo1,2;FENG Quanyuan1   

  1. (1. School of Information Sci. & Tech., Southwest Jiaotong Univ., Chengdu  610031, China|
    2. School of Electric Information, Xihua Univ., Chengdu  610039, China)
  • Received:2010-06-29 Online:2011-06-20 Published:2011-07-14
  • Contact: WANG Weibo

摘要:

针对目前粒子群优化算法在多零点低旁瓣约束的阵列天线方向图综合中早熟收敛、易陷入局部极值的问题,融合混沌优化算法和粒子群优化算法的优点,提出了一种新的混合优化算法.当种群进化停滞时,新算法在种群最优位置的邻域内进行混沌搜索以寻找更优解,其混沌搜索范围可自适应地调整.新的种群最优位置在更新其每一维分量时,选取不同的粒子作为学习对象,提高了粒子的多样性.将此算法应用于阵列天线方向图综合中,能有效地生成多零陷,并抑制旁瓣.

关键词: 混沌理论, 粒子群优化算法, 天线阵列

Abstract:

According to the prematurity and easy trapping in local optimum resulting from using Particle Swarm Optimization(PSO) in the pattern synthesis of antenna arrays with sidelobe reduction and nulls control, a mixed optimal algorithm(Chaotic PSO,CPSO) is proposed by fusing the advantages of both chaotic optimal algorithm and PSO algorithm. The new algorithm uses chaotic searching strategy within the neighborhood of the global best position to find a better solution when the swarm traps into stagnancy. The range of the chaotic searching region can be adaptively adjusted. To enhance the diversity of samples, several individuals are picked out as exemplars when the new global best position is updated in each dimension. Simulation results show that the algorithm can lead to a relatively high performance by applying CPSO in the pattern synthesis of antenna arrays.

中图分类号: 

  • TP820.1