Magnetic dipole localization based on improved roughening particle filter

被引:0
|
作者
Department of Weapon Engineering, Naval University of Engineering, Wuhan [1 ]
430033, China
不详 [2 ]
430070, China
机构
来源
Huazhong Ligong Daxue Xuebao | / 9卷 / 76-80期
关键词
Kullback-Leibler - Magnetic dipole - Particle filter - Roughening - Stochastic filtering;
D O I
10.13245/j.hust.140917
中图分类号
学科分类号
摘要
To address the problem of low accuracy and filtering divergence existed in general nonlinear application to magnetic dipole target tracking, an improved roughening particle filter was proposed to address magnetic dipole tracking problem. The continuous time filtering method was introduced into the framework of roughening particle filter, and an optimal control quantity in K-L (Kullback-Leibler) divergency sense was computed to serve as the mean value in roughening procedure based on Euler discretization to address the particle degeneracy. The continuous time state-space model of magnetic dipole tracking was established, and the concrete implementation of proposed algorithm was presented. A simulation experiment was implemented to compare the proposed algorithm with present magnetic dipole tracking algorithm, and the results demonstrate that the proposed algorithm performs better than present method with preferable accuracy and stability.
引用
收藏
相关论文
共 50 条
  • [1] AN IMPROVED PDR LOCALIZATION ALGORITHM BASED ON PARTICLE FILTER
    Wang, Wei
    Wang, Cunhua
    Wang, Zhaoba
    Zhao, Xiaoqian
    COMPUTING AND INFORMATICS, 2020, 39 (1-2) : 340 - 360
  • [2] An improved particle filter for mobile robot localization based on particle swarm optimization
    Zhang, Qi-bin
    Wang, Peng
    Chen, Zong-hai
    EXPERT SYSTEMS WITH APPLICATIONS, 2019, 135 : 181 - 193
  • [3] A BEAMFORMING PARTICLE FILTER FOR EEG DIPOLE SOURCE LOCALIZATION
    Mohseni, Hamid R.
    Ghaderi, Foad
    Wilding, Edward E.
    Sanei, Saeid
    2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS, 2009, : 337 - +
  • [4] Unscented particle filter for tracking a magnetic dipole target
    Birsan, Marius
    OCEANS 2005, VOLS 1-3, 2005, : 1656 - 1659
  • [5] Mobile robot simultaneous localization and map building based on improved particle filter
    Department of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
    High Technol Letters, 2006, 4 (385-391):
  • [6] Simultaneous Localization and Mapping for Mobile Robot Based on an Improved Particle Filter Algorithm
    Wang, Zhong Min
    Miao, De Hua
    Du, Zhi Jiang
    2009 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION, VOLS 1-7, CONFERENCE PROCEEDINGS, 2009, : 1106 - +
  • [7] Sonar-based AUV localization using an improved particle filter approach
    Maurelli, Francesco
    Petillot, Yvan
    Mallios, Angelos
    Ridao, Pere
    Krupinski, Szymon
    OCEANS 2009 - EUROPE, VOLS 1 AND 2, 2009, : 718 - +
  • [8] A Localization Based on Unscented Kalman Filter and Particle Filter Localization Algorithms
    Ullah, Inam
    Shen, Yu
    Su, Xin
    Esposito, Christian
    Choi, Chang
    IEEE ACCESS, 2020, 8 : 2233 - 2246
  • [9] Service Robot Localization Using Improved Particle Filter
    Cen, Guanghui
    Matsuhira, Nobuto
    Hirokawa, Junko
    Ogawa, Hideki
    Hagiwara, Ichiro
    2008 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6, 2008, : 2454 - +
  • [10] Improved distributed particle filter for simultaneous localization and mapping
    Wu, Mei
    Pei, Fujun
    Telkomnika - Indonesian Journal of Electrical Engineering, 2013, 11 (12): : 7617 - 7626