J4 ›› 2009, Vol. 27 ›› Issue (05): 493-.

• 论文 • 上一篇    下一篇

基于PSO-PTS算法的E形双频微带天线设计

邸朝生1|朱人杰2|曲仁慧3
  

  1. 1.吉林长邮通信建设有限公司| 长春 130012;2.山东邮电规划设计院有限公司| 济南 250031;
    3.吉林大学 通信工程学院|长春 130012
  • 出版日期:2009-09-20 发布日期:2009-11-03
  • 通讯作者: 邸朝生(1955— ),男,吉林榆树人,吉林长邮通信建设有限公司高级工程师,主要从事通信工程研究 E-mail:dichaosheng@163.com
  • 作者简介:邸朝生(1955— )|男|吉林榆树人|吉林长邮通信建设有限公司高级工程师|主要从事通信工程研究(Tel)86-13304308279,(E-mail)dichaosheng@163.com。

Design of EShaped Dual-Frequency Microstrip Antenna Based on PSO-PTS Algorithm

DI Chao-sheng1|ZHU Ren-jie2|QU |Ren-Hui3
  

  1. 1.Jilin Changyou Communications Construction |Limited Liability Company, Changchun 130012, China|2.Shandong Post and Telecommunications Planning and Designing Institute Limited Liability Company| Jinan 250031, China;3.College of Communication Engineering, Jilin University,Changchun 130012,China
  • Online:2009-09-20 Published:2009-11-03

摘要:

为了能处理复杂的电磁优化问题,从粒子群优化算法(PSO:Particle Swarm Optimization )的原理出发,通过对算法收敛性以及算法局限性的分析,改进了粒子群的性能,并结合参数跟踪策略(PTS:Parameters Tracking Strategies)及动态搜索域形成一种新的混合算法——PSOPTS混合算法。给出了PSO-PTS混合算法的基本理论、数学模型和步骤,并利用该方法对E形双频微带天线进行了模拟实验。仿真结果表明,该方法可有效地缩小PSO算法搜索区域,保证了解的单一性,提高了运算速度和解的精度。利用该方法设计的天线可有效地实现小型化的要求。

关键词: 粒子群优化算法, 参数跟踪, 微带天线, 双频

Abstract:

In order to deal with the optimization of complex electromagnetic problems, beginning with the theory of particle swarm optimization, by analyzing the convergence of the algorithm and its limitations, the performance of PSO (Particle Swarm Optimization )was improved, parameters tracking was combined, and PSO-PTS (Particle Swarm Optimization Parameters Tracking Strategies)hybrid algorithm was proposed. The method can effectively reduce the search region of PSO algorithm, ensure the uniformity of solution, enhance the computing speed and the accuracy of solution. Basic theory, math model and predict step of the algorithm was introduced. E-shaped dualfrequency microstrip antenna by using PSO-PTS hybrid algorithm was simulated. The results show that the antenna designed by this metheod can sufficiently realize the demand of miniaturization. 

Key words: particle swarm optimization, parameters tracking, microstrip antenna, dualfrequency

中图分类号: 

  • TN82