西安电子科技大学学报 ›› 2021, Vol. 48 ›› Issue (4): 57-63.doi: 10.19665/j.issn1001-2400.2021.04.008

• 信息与通信工程&电子科学与技术 • 上一篇    下一篇

区域能量聚焦技术中超稀疏阵列优化算法

杨仲平(),周青松(),张剑云()   

  1. 国防科技大学 电子对抗学院,安徽 合肥 230031
  • 收稿日期:2020-07-11 出版日期:2021-08-30 发布日期:2021-08-31
  • 作者简介:杨仲平(1996—),男,国防科技大学硕士研究生,E-mail: yangzhongping14@nudt.edu.cn|周青松(1982—),男,副教授,博士,E-mail: zhouqingsong1207@gmail.com|张剑云(1963—),男,教授,博士,E-mail: zjy921@sina.com
  • 基金资助:
    安徽省自然科学基金(1908085QF252);国防科技大学校研计划(ZK19-10)

Optimization algorithm for ultra-sparse arrays in regional energy focusing

YANG Zhongping(),ZHOU Qingsong(),ZHANG Jianyun()   

  1. College of Electronic Engineering,National University of Defense Technology,Hefei 230031,China
  • Received:2020-07-11 Online:2021-08-30 Published:2021-08-31

摘要:

超稀疏阵列设置是影响区域能量聚焦性能的关键因素。以无人机实施精确电子战为典型应用背景,提出一种区域能量聚焦技术中超稀疏阵列优化算法,以最大化区域能量聚焦效果。首先对超稀疏阵列优化问题建立干扰信号与各阵元位置的联合优化模型;然后采用粒子群算法对阵元位置进行迭代求解;接下来在每个迭代过程中,针对已知的阵元位置求解干扰波形子问题,将子问题的目标值作为粒子群算法的适应度准则,最终得到超稀疏阵列与干扰信号的最优解。仿真实验表明,该方法能有效优化超稀疏阵列,提升精确电子战中的多项评估指标。在各阵元有定位误差和无定位误差两种情况下,均比现有仅设计干扰信号的算法具有更好的精确干扰性能。

关键词: 区域能量聚焦, 超稀疏阵列, 粒子群算法, 优化算法

Abstract:

The setting of ultra-sparse arrays is one of key factors for the performance of regional energy focusing.This paper focuses on one of its typical applications:Precision Electronic Warfare by UAV,and proposes an optimization algorithm for ultra-sparse arrays to maximize the performance of regional energy focusing.First,we establish the joint optimization model of the interference waveform and the positions of elements.Second,particle swarm optimization (PSO) is adopted to iterate the positions of elements.Then,the target value of the subproblem is solved for the fitness criterion,as the current array is known in each step of the iteration.Finally,we get the optimal solution of the interference waveform and the ultra-sparse array by this method.Numerical results indicate that the algorithm can optimize the array effectively,and improve the indicators of regional energy focusing obviously.Whether the localization errors of elements exist or not,the algorithm provides a better performance than existing algorithms which only design the interference waveform.

Key words: regional energy focusing, ultra-sparse arrays, particle swarm optimization, optimization algorithm

中图分类号: 

  • TN972