一种基于信息熵的雷达动态自适应选择跟踪方法

葛建军 李春霞

葛建军, 李春霞. 一种基于信息熵的雷达动态自适应选择跟踪方法[J]. 雷达学报, 2017, 6(6): 587-593. doi: 10.12000/JR17081
引用本文: 葛建军, 李春霞. 一种基于信息熵的雷达动态自适应选择跟踪方法[J]. 雷达学报, 2017, 6(6): 587-593. doi: 10.12000/JR17081
Ge Jianjun, Li Chunxia. A Dynamic and Adaptive Selection Radar Tracking Method Based on Information Entropy[J]. Journal of Radars, 2017, 6(6): 587-593. doi: 10.12000/JR17081
Citation: Ge Jianjun, Li Chunxia. A Dynamic and Adaptive Selection Radar Tracking Method Based on Information Entropy[J]. Journal of Radars, 2017, 6(6): 587-593. doi: 10.12000/JR17081

一种基于信息熵的雷达动态自适应选择跟踪方法

DOI: 10.12000/JR17081
基金项目: 装发预研重点基金项目(6140-4130-1021-6DZ9-1001)
详细信息
    作者简介:

    葛建军(1967–),男,研究员,研究方向为雷达系统

    李春霞(1987–),女,北京理工大学博士,高级工程师,研究方向为网络化雷达、信息融合、信息论

    通讯作者:

    李春霞   yunhai_cetc@163.com

A Dynamic and Adaptive Selection Radar Tracking Method Based on Information Entropy

Funds: Key Projects of Equipment Forecast Fund of the General Armament Department (6140-4130-1021-6DZ9-1001)
  • 摘要:

    在现代战争中,战场环境复杂多变,为适应战场探测资源动态组织,基于信息熵,该文提出了定量度量多雷达联合观测获得目标信息量多少的方法,并给出了该信息量的下界。进而,基于最小化每个时刻多雷达观测获得的目标信息熵下界,提出了一种自适应选取信息含量高的雷达进行目标跟踪的方法。仿真结果表明,相比不采用信息熵的跟踪方法,提出的方法具有更高的跟踪精度。

     

  • 图  1  4部雷达位置与目标航迹图

    Figure  1.  Radars locations and target trajectory

    图  2  不同时刻选择的信息量高的雷达编号

    Figure  2.  Radars indexes selected by fusion entropy model

    图  3  目标位置跟踪精度对比

    Figure  3.  Comparison of target position RMSE

    图  4  目标速度跟踪精度对比

    Figure  4.  Comparison of target velocity RMSE

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出版历程
  • 收稿日期:  2017-09-08
  • 修回日期:  2017-11-16
  • 网络出版日期:  2017-12-28

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