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双层无迹卡尔曼滤波

杨峰 郑丽涛 王家琦 潘泉

杨峰, 郑丽涛, 王家琦, 潘泉. 双层无迹卡尔曼滤波. 自动化学报, 2019, 45(7): 1386-1391. doi: 10.16383/j.aas.c180349
引用本文: 杨峰, 郑丽涛, 王家琦, 潘泉. 双层无迹卡尔曼滤波. 自动化学报, 2019, 45(7): 1386-1391. doi: 10.16383/j.aas.c180349
YANG Feng, ZHENG Li-Tao, WANG Jia-Qi, PAN Quan. Double Layer Unscented Kalman Filter. ACTA AUTOMATICA SINICA, 2019, 45(7): 1386-1391. doi: 10.16383/j.aas.c180349
Citation: YANG Feng, ZHENG Li-Tao, WANG Jia-Qi, PAN Quan. Double Layer Unscented Kalman Filter. ACTA AUTOMATICA SINICA, 2019, 45(7): 1386-1391. doi: 10.16383/j.aas.c180349

双层无迹卡尔曼滤波

doi: 10.16383/j.aas.c180349
基金项目: 

西北工业大学创新创意种子基金 zz2018149

光电控制技术重点实验室和航空科学基金联合 20165153034

中国电子科技集团公司数据链技术重点实验室开放基金 CLDL-20182203

国家自然科学基金 61374159

陕西省自然基金 2018MJ6048

详细信息
    作者简介:

    郑丽涛   西北工业大学硕士研究生.主要研究方向为信息融合, 目标跟踪, 雷达数据处理.E-mail:zhenglitao@mail.nwpu.edu.cn

    王家琦   西北工业大学硕士研究生.主要研究方向为信息融合, 目标跟踪, 雷达数据处理.E-mail:jackwang@mail.nwpu.edu.cn

    潘泉   西北工业大学自动化学院教授.主要研究方向为目标跟踪, 信息融合, 复杂系统估计.E-mail:quanpan@nwpu.edu.cn

    通讯作者:

    杨峰   西北工业大学自动化学院副教授.主要研究方向为多源信息融合, 目标跟踪, 雷达数据处理.本文通信作者.E-mail:yangfeng@nwpu.edu.cn

Double Layer Unscented Kalman Filter

Funds: 

the Seed Foundation of Innovation and Creation for Graduate Students in Northwestern Polytechnical University zz2018149

Science and Technology on Electro-optic Control Laboratory, Aviation Science Foundation 20165153034

the Open Foundation of CETC Key Laboratory of Data Link Technology CLDL-20182203

National Natural Science Foundation of China 61374159

Shaanxi Natural Fund 2018MJ6048

More Information
    Author Bio:

      Master student at the School of Automation, Northwestern Polytechnical University. His research interest covers target tracking, information fusion, and radar data processing

      Master student at the School of Automation, Northwestern Polytechnical University. His research interest covers target tracking, information fusion, and radar data processing

      Professor at the School of Automation, Northwestern Polytechnical University. His research interest covers target tracking, information fusion, and hybrid system estimation theory

    Corresponding author: YANG Feng   Associate professor at the School of Automation, Northwestern Polytechnical University. His research interest covers information fusion, target tracking, and radar data processing. Corresponding author of this paper
  • 摘要: 针对无迹卡尔曼滤波(Unscented Kalman fllter,UKF)在强非线性系统中估计效果差的问题,提出了双层无迹卡尔曼滤波(Double layer unscented Kalman filter,DLUKF)算法,该算法用带权值的采样点表征先验分布,而后用内层UKF算法对每个采样点进行更新,最后引入外层UKF算法的更新机制得到估计值和估计协方差.仿真结果表明,相比于传统算法,所提的DLUKF算法可以在较低计算负载下获得较高滤波估计精度.
    1)  本文责任编委 朱纪洪
  • 图  1  DLUKF算法流程图

    Fig.  1  The flow-chart of DLUKF

    图  2  300次蒙特卡洛仿真的RMSE

    Fig.  2  The calculation time and RMSE of each algorithm

    图  3  位置的RMSE

    Fig.  3  The RMSE of position

    表  1  各算法计算时间及RMSE对比分析表

    Table  1  The calculation time and RMSE of each algorithm

    算法 运行时间(s) 平均RMSE
    UKF 0.0002 0.1566
    IUKF 0.0014 0.0881
    RUEKF 0.0006 0.0378
    RUCKF 0.0031 0.0337
    高阶UKF 0.0006 0.1434
    高阶CKF 0.0006 0.1437
    UPF (100) 0.1032 0.1153
    UPF (200) 0.2097 0.0714
    UPF (300) 0.3200 0.0626
    UPF (400) 0.4296 0.0564
    UPF (500) 0.5416 0.0476
    DLUKF 0.0016 0.0297
    下载: 导出CSV

    表  2  仿真参数设置

    Table  2  The Simulation parameters

    参数 $T$ $q$ ${\sigma _{1r}}$ ${\sigma _{1\varepsilon }}$ ${\sigma _{2r}}$ ${\sigma _{2\varepsilon }}$ $\varepsilon $
    数值 1 1 20 m 0.2$^{o}$ 200 m 0.2$^{o}$ 0.1
    下载: 导出CSV

    表  3  各个算法的性能

    Table  3  The performance of each algorithm

    算法 运行时间(s) 平均RMSE
    UKF 0.0059 99.8709
    IUKF 0.0424 85.0107
    RUEKF 0.0150 100.2616
    RUCKF 0.0397 99.8704
    高阶UKF 0.0193 100.4763
    高阶CKF 0.0191 99.7558
    UPF (300) 3.5953 88.2638
    UPF (400) 4.8406 86.5004
    UPF (500) 6.0552 85.8206
    UPF (600) 7.2596 85.1056
    UPF (700) 8.4211 84.6700
    UPF (800) 9.6178 83.2706
    UPF (900) 10.8389 82.9057
    UPF (1 000) 12.0105 82.4258
    DLUKF 0.0757 78.5559
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-05-26
  • 录用日期:  2018-10-09
  • 刊出日期:  2019-07-20

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