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

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

葛建军,
李春霞^,

中国电子科技集团公司信息科学研究院北京 100081

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

计量
- 文章访问数: 1987
- HTML全文浏览量: 594
- PDF下载量: 498
- 被引次数: 0
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

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

Ge Jianjun,
Li Chunxia^,

Information Science Academy, China Electronics Technology Group Corporation, Beijing 100081, China

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

摘要

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。
- 多雷达 /
- 信息论 /
- 目标跟踪
Abstract:
Nowadays, the battlefield environment has become much more complex and variable. This paper presents a quantitative method and lower bound for the amount of target information acquired from multiple radar observations to adaptively and dynamically organize the detection of battlefield resources based on the principle of information entropy. Furthermore, for minimizing the given information entropy’s lower bound for target measurement at every moment, a method to dynamically and adaptively select radars with a high amount of information for target tracking is proposed. The simulation results indicate that the proposed method has higher tracking accuracy than that of tracking without adaptive radar selection based on entropy.
- Multi-static radar /
- Information entropy /
- Target tracking

HTML全文

图 1 4部雷达位置与目标航迹图

Figure 1. Radars locations and target trajectory

下载: 全尺寸图片幻灯片

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

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图 3 目标位置跟踪精度对比

Figure 3. Comparison of target position RMSE

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图 4 目标速度跟踪精度对比

Figure 4. Comparison of target velocity RMSE

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参考文献(14)

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