• 中国科技核心期刊
  • JST收录期刊
Volume 21 Issue 5
 
Turn off MathJax
Article Contents
Article Navigation >  Journal of Unmanned Undersea Systems  > 2013  >  21(5): 351-354
LIU Ming-yong, GUO Yong, ZHANG Li-chuan, GAO Pei-lin. UKF-Based Algorithm for MEMS/GPS Integrated Navigation System[J]. Journal of Unmanned Undersea Systems, 2013, 21(5): 351-354. doi: 10.11993/j.issn.1673-1948.2013.05.007
Citation: LIU Ming-yong, GUO Yong, ZHANG Li-chuan, GAO Pei-lin. UKF-Based Algorithm for MEMS/GPS Integrated Navigation System[J]. Journal of Unmanned Undersea Systems, 2013, 21(5): 351-354. doi: 10.11993/j.issn.1673-1948.2013.05.007
shu

UKF-Based Algorithm for MEMS/GPS Integrated Navigation System

doi: 10.11993/j.issn.1673-1948.2013.05.007
  • 1.

    College of Marine Engineering, Northwestern Polytechnical University, Xi′an 710072, China

  • 2.

    Science and Tech-nology on Underwater Information and Control Laboratory, Xi′an 710072, China

  • Received Date: 2012-12-26
  • Rev Recd Date: 2013-03-28
  • Publish Date: 2013-10-20
    Abstract
  • To solve the problems of low navigation accuracy, slow convergence rate and unstable filtering accuracy caused by the strong nonlinearity of the extended Kalman filter(EKF) in micro electro mechanical system/global posi-tioning system(MEMS/GPS) integrated navigation system, an unscented Kalman filter(UKF) is proposed for the MEMS/GPS integrated navigation system. The UKF avoids the heavy derivation in EKF. Simulation results show that the two filtering methods: the error convergence rate of UKF integrated navigation system is faster, the accuracy is higher than the EKF. Comparison between the two algorithms shows that MEMS/GPS integrated navigation system with UKF achieves faster error convergence rate, higher navigation accuracy and enhanced navigation performance.

     

    • FullText(HTML)
  • loading
    • References(9)
  • [1]
    秦永元, 张洪钺, 汪叔华．卡尔曼滤波与组合导航原理[M]．西安: 西北工业大学出版社, 1998.
    [2]
    曹学伟, 石杏喜, 左常清. 基于EKF的DR/激光测距组合导航算法研究[J]. 山东科技大学学报, 2009(2): 84-87.

    Cao Xue-wei, Shi Xing-xi, Zuo Chang-qing. Study on DR/Laser Rangefinder Integrated Navigation Algorithm Based on EKF[J]. Journal of Shandong University of Science and Technology, 2009(2): 84-87.
    [3]
    Quinchia A G, Carles F. Analysis and Modelling of MEMS Inertial Measurement Unit[C]//Localization and GNSS (ICL- GNSS), 2012 International Conference, 2012: 1-7.
    [4]
    Julier S, Uhlmann J K. A General Method for Approxi-mating Nonlinear Transformations of Probability Distri-butions[R]. Robotics Research Group, Department of En-gineering Science, University of Oxford, 1994.
    [5]
    Uhlmann J K. Simultaneous Map Building and Localiza-tion for Real Time Applications[R]. U.K: University of Oxford, 1994.
    [6]
    Saeedi Sara, EI-Sheimy. The Merits of UKF and PF for Integrated INS/GPS Navigation Systems[C]//22nd Inter-national Technical Meeting of the Satellite Division of the Institute of Navigation, 2009: 1612-1618.
    [7]
    Li Tao, Xu Xiao-su. The Application of EKF and UKF to the SINS/GPS Integrated Navigation Systems[C]//Infor- mation Engineering and Computer Science(ICIECS), 2010 2nd International Conference, 2010: 25-26.
    [8]
    李涛. 非线性滤波方法在导航系统中的应用研究[D]. 长沙: 国防科学技术大学, 2003.
    [9]
    张红梅, 邓正隆. UKF方法在陆地车辆组合导航中的应用[J]. 中国惯性技术学报, 2004, 16(4): 20-23.

    Zhang Hong-mei, Deng Zheng-long. UKF Method for Land Vehicle Integrated Navigation System[J]. Journal of Chinese Inertial Technology, 2004, 16(4): 20-23.
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Get Citation
    PDF
    XML

    Article Metrics

    Article Views(835) PDF Downloads(418) Cited by()
    Proportional views
    Related
    Service
    Subscribe
    Copyright：陕ICP备09015163号Address:No. 96, Jinye Road, Xi'an, Shaanxi
    Code：710077Tel: 029-88327279QQ: 767358370
    Email: bianjibu705@sohu.com 767358370@qq.com
    Email Alert RSS
    Taobao
    Micro

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return