• DocumentCode
    536537
  • Title

    Study on the Adaptive Partial Systematic Resampling Algorithm of Particle Filter

  • Author

    Liu, Wenjing ; Yu, Jinxia ; Xu, Jingmin

  • Author_Institution
    Coll. of Comput. Sci. & Technol., Henan Polytech. Univ., Jiaozuo, China
  • fYear
    2010
  • fDate
    7-9 Nov. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Sample degeneracy is a major problem of particle filter which is based on the sequential importance sampling. In order to solve this problem, the resampling algorithm is introduced in particle filter. Regular resampling algorithm can solve the sample degradation, but it easily lead to sample depletion and increase the computing complexity. The adaptive partial systematic resampling (APSR) algorithm adjusts the resampling time adaptively, before the resampling, classified the particles according to the weight, resampling is carries on the minority particles, The simulation result indicated that it increase the particle diversity and reduces the computation time.
  • Keywords
    computational complexity; particle filtering (numerical methods); sampling methods; adaptive partial systematic resampling algorithm; computing complexity; particle filter; sample degeneracy; sample degradation; sequential importance sampling; Adaptive systems; Bayesian methods; Classification algorithms; Mathematical model; Monte Carlo methods; Particle filters; Systematics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on
  • Conference_Location
    Henan
  • Print_ISBN
    978-1-4244-7159-1
  • Type

    conf

  • DOI
    10.1109/ICEEE.2010.5660244
  • Filename
    5660244