北京航空航天大学学报 ›› 2006, Vol. 32 ›› Issue (08): 933-936.

• 论文 • 上一篇    下一篇

遗传算法在电子战干扰规划中的应用

高彬1, 吕善伟1, 郭庆丰2, 张娜2   

  1. 1. 北京航空航天大学 电子信息工程学院, 北京 100083;
    2. 空军装备研究所 雷达所, 北京 100085
  • 收稿日期:2005-10-17 出版日期:2006-08-31 发布日期:2010-09-19
  • 作者简介:高 彬(1977-), 男, 山东济南人, 博士生, gaobin@ee.buaa.edu.cn.

Genetic algorithm approach to the jammer′s layout for EW

Gao Bin1, Lü Shanwei1, Guo Qingfeng2, Zhang Na2   

  1. 1. School of Electronics and Information Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China;
    2. The Radar Institute, Equipment Academy of Air Force, Beijing 100085, China
  • Received:2005-10-17 Online:2006-08-31 Published:2010-09-19

摘要: 电子对抗干扰资源任务规划问题对于充分发挥干扰机作战效能,取得最佳干扰效益有重要作用.结合现代电子战特点,利用搜索论推导出了干扰机压制概率的计算公式,建立了干扰任务分配模型,并阐述了传统匈牙利方法在这一问题处理上的局限性.结合智能优化算法,提出了基于遗传算法的干扰资源优化分配模型.解决了优化分配模型所需的符号编码方式,并给出了相关的选择、交叉、变异等遗传算子的具体设计.利用该模型,解决了2个实例.结果表明,该模型在干扰资源任务配置问题上具有很强的实用性,遗传算法可以有效地辅助指挥员解决干扰资源部署决策这一复杂而困难的问题.

Abstract: The assignment problem of jamming resource for electronic warfare(ECM) plays a key role in utilizing jammer sufficiently and obtaining the optimal jamming effect. According to characteristics of modern electronic warfare(EW), the calculation formula of jammer′s avoidance ratio was investigated by use of search theory. The jamming force optimization apportion model was presented, and the limitation for Hungary method in settling this problem was illustrated. So combined with the intelligent optimization algorithm, a jamming force optimization apportion model based on genetic algorithm(GA) was presented. The symbol encoding style what was needed for the optimization apportion model was solved, and selection operator, cross operator and mutation operator were designed concretely. Two application examples were resolved using this model. The results show good practicability of the model, and the GA presented is effective and practical. GA can efficiently help commanders solve the complicate and difficult problem of jammer′s layout.

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