系统工程与电子技术 ›› 2021, Vol. 43 ›› Issue (10): 2697-2705.doi: 10.12305/j.issn.1001-506X.2021.10.01

• 电磁散射与逆散射研究新进展专栏 •    下一篇

基于模式/区域分解的无人机集群电磁特性快速分析

管灵, 朱晨曦, 董纯柱*, 殷红成   

  1. 北京环境特性研究所, 北京 100854
  • 收稿日期:2020-12-28 出版日期:2021-10-18 发布日期:2021-10-18
  • 通讯作者: 董纯柱
  • 作者简介:管灵(1991—), 男, 工程师, 博士, 主要研究方向为计算电磁学、电磁散射|朱晨曦(1994—), 女, 助理工程师, 硕士, 主要研究方向为计算电磁学、电磁散射|董纯柱(1981—), 男, 研究员, 博士, 主要研究方向为电磁散射与逆散射、雷达目标识别|殷红成(1967—), 男, 研究员, 博士, 主要研究方向为电磁散射与逆散射、雷达目标识别、隐身技术

Fast analysis of electromagnetic characteristics for UAV groups based on mode and domain decomposition

Ling GUAN, Chenxi ZHU, Chunzhu DONG*, Hongcheng YIN   

  1. Beijing Institute of Environmental Characteristics, Beijing 100854, China
  • Received:2020-12-28 Online:2021-10-18 Published:2021-10-18
  • Contact: Chunzhu DONG

摘要:

无人机(unmanned aerial vehicle, UAV)集群在军事和民用领域的应用越来越广泛, 针对UAV集群目标电磁散射特性的获取和分析对生成对抗策略及反UAV有着重要的研究价值。目前, UAV集群动态测量数据获取难度较大、成本高; 而对于仿真数据, 传统计算电磁方法建模精度和效率较低, 有效的特性数据不足。因此, 提出了一种基于模式/区域分解的UAV集群目标电磁仿真方法, 该方法在矩量法的基础上, 引入特征模分解和区域分解技术, 前者极大地降低了计算未知量, 后者有效地解决了建模精度问题, 为UAV集群目标特性数据的生成提供了创新技术支撑。

关键词: 无人机集群, 电磁散射特性, 模式分解, 区域分解

Abstract:

Unmanned aerial vehicle (UAV) groups have been widely used in the modern society and military. The acquisition and analysis of the electromagnetic scattering characteristics of UAV group targets has important research value for anti-UAV. At present, the valid scattering data of UAV groups is insufficient because the acquisition of dynamic measurement data is difficult and costly. And for the simulation data, traditional computational electromagnetic methods lack modeling accuracy and efficiency. Therefore, a electromagnetic simulation method of UAV cluster target based on the mode and domain decomposition is proposed to solve this problem. This method reduces the number of unknowns greatly by using characteristic modes. and increases the modeling accuracy by introducing the eigenmode decomposition and the domain decomposition method. It provides a new technical support for the generation of electromagnetic scattering data of UAV groups.

Key words: unmanned aerial vehicle (UAV) group, electromagnetic scattering characteristics, mode decomposition, domain decomposition

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