• DocumentCode
    2231489
  • Title

    Comparison of resampling schemes for particle filtering

  • Author

    Douc, R. ; Cappe, Olivier

  • Author_Institution
    Ecole Polytech., Palaiseau, France
  • fYear
    2005
  • fDate
    15-17 Sept. 2005
  • Firstpage
    64
  • Lastpage
    69
  • Abstract
    This contribution is devoted to the comparison of various resampling approaches that have been proposed in the literature on particle filtering. It is first shown using simple arguments that the so-called residual and stratified methods do yield an improvement over the basic multinomial resampling approach. A simple counter-example showing that this property does not hold true for systematic resampling is given. Finally, some results on the large-sample behavior of the simple bootstrap filter algorithm are given. In particular, a central limit theorem is established for the case where resampling is performed using the residual approach.
  • Keywords
    Monte Carlo methods; particle filtering (numerical methods); signal sampling; bootstrap filter algorithm; multinomial resampling approach; particle filtering; resampling schemes; residual methods; sequential Monte Carlo methods; stratified methods; Computational modeling; Density functional theory; Filtering; Filters; Image processing; Monte Carlo methods; Signal processing; Signal processing algorithms; Sliding mode control; State estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing and Analysis, 2005. ISPA 2005. Proceedings of the 4th International Symposium on
  • ISSN
    1845-5921
  • Print_ISBN
    953-184-089-X
  • Type

    conf

  • DOI
    10.1109/ISPA.2005.195385
  • Filename
    1521264