• DocumentCode
    2555529
  • Title

    Interacting multiple model gaussian particle filter

  • Author

    Liu, Zhigang ; Wang, Jinkuan

  • Author_Institution
    Insitute of Eng. Optimization & Smart Antenna, Northeastern Univ., Qinhuangdao, China
  • fYear
    2011
  • fDate
    21-25 June 2011
  • Firstpage
    270
  • Lastpage
    273
  • Abstract
    For maneuvering target tracking, the interacting multiple model Gaussian particle filter is proposed without resampling, which can avoid the degeneracy in the effective number of particles. The basic idea is to combine the interacting multiple model approach with a Gaussian particle filter and this approach is easy of parallel implementation. Finally, simulation results show the effectiveness of the proposed algorithms.
  • Keywords
    Gaussian processes; particle filtering (numerical methods); target tracking; multiple model Gaussian particle filter; parallel implementation; target tracking maneuvering; Acceleration; Approximation methods; Equations; Markov processes; Mathematical model; Noise; Target tracking; Gaussian particle filter; Maneuvering target tracking; interacting multiple model; resampling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation (WCICA), 2011 9th World Congress on
  • Conference_Location
    Taipei
  • Print_ISBN
    978-1-61284-698-9
  • Type

    conf

  • DOI
    10.1109/WCICA.2011.5970741
  • Filename
    5970741