• DocumentCode
    3418915
  • Title

    Multirate Interacting Multiple Model Algorithm Combined with Particle Filter for Nonlinear/Non-Gaussian Target Tracking

  • Author

    Liu, Guixi ; Gao, Enke ; Fan, Chunyu

  • Author_Institution
    Dept. of Autom., Xidian Univ., Xi´´an
  • fYear
    2006
  • fDate
    Nov. 29 2006-Dec. 1 2006
  • Firstpage
    298
  • Lastpage
    301
  • Abstract
    In this paper, we propose a new interacting multiple model (IMM) algorithm combined with particle filter for nonlinear/non-Gaussian systems, which adopts the multirate technique to improve the computational efficiency. The interacting multiple model (IMM) algorithm is specially designed to track accurately targets, and the particle filter is aim to deal with nonlinear/non-Gaussian problems. But the problem of a particle filter is its expensive computation, especially when it is introduced into the IMM algorithm. Here, the multirate technique is to solve this problem and not making the performance of the algorithm bad. The experimental results show the multirate IMMPF (IMM particle filter) works as well as IMMPF with much lower computation load.
  • Keywords
    Gaussian processes; particle filtering (numerical methods); target tracking; multirate interacting multiple model algorithm; nonlinear/nonGaussian target tracking; particle filter; Algorithm design and analysis; Automation; Computational efficiency; Equations; Filtering algorithms; Particle filters; Particle tracking; Performance analysis; Steady-state; Target tracking; computation; interacting multiple model; multirate; nonlinear/non-Gaussian target tracking; particle filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Reality and Telexistence--Workshops, 2006. ICAT '06. 16th International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    0-7695-2754-X
  • Type

    conf

  • DOI
    10.1109/ICAT.2006.92
  • Filename
    4089261