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兵工学报 ›› 2013, Vol. 34 ›› Issue (3): 332-338.doi: 10. 3969/ j. issn. 1000-1093. 2013. 03. 012

• 研究论文 • 上一篇    下一篇

多波束干扰系统干扰资源综合管理算法

宋海方, 吴华, 程嗣怡, 陈游   

  1. 空军工程大学航空航天工程学院, 陕西西安710038
  • 上线日期:2013-07-23
  • 通讯作者: 宋海方 E-mail:simlife261@ qq. com
  • 作者简介:宋海方(1989—), 男, 硕士研究生。
  • 基金资助:

    陕西省自然科学基金项目(2012IQ8019); 电子信息控制国防重点实验室基金课题(9140C1005051103)

Integrated Management Algorithm of Jamming Resources in Multi-beam Jamming Systems

SONG Hai-fang, WU Hua, CHENG Si-yi, CHEN You   

  1. Aeronautics and Astronautics Engineering College, Air Force Engineering University, Shaanxi 710038, Xi'an, China
  • Online:2013-07-23
  • Contact: SONG Hai-fang E-mail:simlife261@ qq. com

摘要:

针对先进战机多波束干扰系统同时干扰多部雷达时的资源管理问题,采用多属性决策 方法建立了战机电子对抗系统威胁等级评估模型,并与神经元模型相结合建立了干扰任务请求模 型;针对干扰资源的限制,对目标雷达进行分类,当需要且能够干扰的雷达数目超出干扰波束数目 时,建立了干扰任务整合模型,并采用C-means 算法对模型进行求解;最后提出了多波束干扰系统 同时干扰多部雷达时的资源管理算法。对目标进行分类和对干扰任务进行整合可以提高多波束干 扰系统的效率,提升干扰系统的智能化水平。

关键词: 雷达工程, 多波束干扰, 干扰目标分类, 干扰任务整合, 聚类分析, 资源管理

Abstract:

To study the integrated management of jamming resources in advanced airborne multi-beam jamming systems, the model of threat assessment is built by means of multiple attribute decision making and the model of jamming task request is set. According to the jamming resources constraints, radar tar- gets classification are achieved. When the jamming task request is beyond the jamming beams, the C-means algorithm to integrate the jamming tasks is used. The algorithm of jamming resources distribution in multi-beam jamming systems is proposed. Target classification and task integration can optimize the use of jamming resources and improve the standard of intelligence in multi-beam jamming systems.

Key words: radar engineering, multi-beam jamming systems, target classification, task integration, cluster analysis, jamming resources distribution

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