基于模糊离散粒子群算法的非均匀阵列优化

阳凯; 赵志钦; 聂在平

doi:10.3969/j.issn.1001-0548.2012.01.009

基于模糊离散粒子群算法的非均匀阵列优化

电子科技大学电子工程学院成都 610054

基金项目:

国家自然科学基金(60927002);高等学校学科创新引智计划(B07046);中央高校基本科研业务费(103.1.2 E022050205)

详细信息

作者简介:
阳凯(1986-),男,博士生,主要从事阵列信号处理及共形天线设计等方面的研究.

中图分类号: TN011
计量
- 文章访问数: 5210
- HTML全文浏览量: 239
- PDF下载量: 80
出版历程
- 收稿日期: 2010-05-05
- 修回日期: 2010-10-07
- 刊出日期: 2012-02-14

Optimization of Unequally Spaced Antenna Arrays Using Fuzzy Discrete Particle Swarm Algorithm

School of Electronic Engineering,University of Electronic Science and Technology of China Chengdu 610054

Funds:

Supported by the National Natural Science Foundation of China (60927002);111Project (B07046); the Fundamental Research Funds for the Central Universities (103.1.2 E022050205).

摘要

摘要: 首次将模糊离散粒子群算法应用到稀疏阵列天线阵元位置优化上,以得到低的副瓣电平。与遗传算法等进化算法相比,模糊离散粒子群算法有参数少、易于执行的优点。为了尽量避免算法陷入局部最优,在优化中引入了混沌过程;同时用罚函数方法进行了主瓣约束。对于线性阵列的仿真结果表明,该方法能很好地处理离散问题。
- 天线综合 /
- 粒子群算法 /
- 罚函数 /
- 稀疏阵列
Abstract: Aiming to obtain a low sidelobe of an array, fuzzy discrete particle swarm optimization (FDPSO) algorithm is firstly applied in the optimization of the element positions of thinned antenna arrays. Compared with some evolutionary algorithms such as genetic algorithm, the FDPSO has the advantages of less parameters and easier to be implemented. In order to avoid the algorithm being trapped into local optimum, a chaotic dynamic procedure is introduced in the optimization. A penalty approach is used in the constraint of the width of mainlobe. Simulation results of a linear array show that the algorithm can handle discrete problem properly.
- array pattern synthesis /
- particle swarm optimization /
- penalty function /
- thinned arrays