• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2014, Vol. 36 ›› Issue (01): 105-110.

• 论文 • 上一篇    下一篇

一种靶场电磁环境复杂度评估方法

彭武1,何怡刚1,2,方葛丰3,樊晓腾3   

  1. (1.湖南大学电气与信息工程学院,湖南 长沙 410082;2. 合肥工业大学电气与自动化工程学院,安徽 合肥 230009;
    3.电子测试技术国防科技重点实验室,山东 青岛266555)
  • 收稿日期:2012-08-13 修回日期:2012-11-13 出版日期:2014-01-25 发布日期:2014-01-25
  • 基金资助:

    国家杰出青年科学基金资助项目(50925727);国家自然科学基金资助项目(60876022,61102039,51107034);湖南省科技计划项目(2011J4,2011JK2023);广东省教育部产学研计划资助项目(2009B090300196);中央高校基本科研业务费计划资助项目

Complexity evaluation method for range electromagnetic environment         

PENG Wu1,HE Yigang1,2,FANG Gefeng3,FAN Xiaoteng3   

  1. (1.College of Electrical and Information Engineering,Hunan University,Changsha 410082;
    2.School of Electrical and Automation Engineering,Hefei University of Technology,Hefei 230009;
    3.National Key Laboratory of Science & Technology on Electronic Test & Measurement,Qingdao 266555,China)
  • Received:2012-08-13 Revised:2012-11-13 Online:2014-01-25 Published:2014-01-25

摘要:

针对电磁环境越来越复杂的问题,提出了一种基于前馈BP神经网络算法的电磁环境复杂度评估方法。首先建立了靶场电磁环境模型,分析了电磁环境复杂度的评估指标,为定量评估提供理论依据;然后分析了BP神经网络关键参数的选取方法,通过靶场实例验证了神经网络的功能;最后将新方法与传统评估方法进行了对比研究。结果表明了新方法优于传统方法,能够实时、快速、自适应地实现电磁环境的定性和定量分级,拓展了传统方法的应用范围,对研究真实的战场电磁环境问题具有实用价值。

关键词: 靶场, 电磁环境, 复杂度, BP神经网络, 复杂度, 收敛速度

Abstract:

The electromagnetic environment has become increasingly complex. In order to evaluate the complexity properly, a new method based on Back Propagation (BP) neural network is proposed. Firstly, the paper establishes range electromagnetic environment model, analyses the electromagnetic environment complexity evaluation index, in order to provide theoretical basis for quantitative evaluation. Secondly, we analyze the selection method of key parameters of BP neural network, and an example is used to verify the neural network function. Finally, the new method and the traditional evaluation methods are compared. Results show that the new method outperforms the traditional methods and realizes qualitative and quantitative classification of the electromagnetic environment in a realtime, fast and self adaptive way. It expands the application range of the traditional methods, and has practical value in studying the complex electromagnetic environment in real battlefield.

Key words: range;electromagnetic environment;back propagation(BP) neural network;complexity;convergence speed