• DocumentCode
    1593426
  • Title

    Particle-Based H-infinity Filter Scheme and Numerical Experiments

  • Author

    Wu Zhuhui ; Han Yueqi

  • Author_Institution
    Jinling Inst. of Technol., Nanjing, China
  • fYear
    2012
  • Firstpage
    439
  • Lastpage
    442
  • Abstract
    The H filter technique, which was developed in signal processing and control field in recent years, is introduced into data fusion method. Based on the principle of particles of forward model, a new sequential data fusion method called "particle H filter" is introduced into this paper by integrating H filter technique and Monte Carlo method. This method can be used for nonlinear systems lacking the statistical properties of observational errors. To find the smallest level factor γ that could bring optimal estimations, bisection search method is embedded in the arithmetic of particle H filter and their calculation steps are also given. The numerical results also show that particle H filter data fusion method is effective and suitable to nonlinear systems in that it does not rely on the statistical properties of observational errors and has better robustness.
  • Keywords
    H filters; Monte Carlo methods; nonlinear control systems; particle filtering (numerical methods); search problems; sensor fusion; signal processing; Monte Carlo method; bisection search method; control field; forward model; nonlinear system; numerical experiments; observational errors; optimal estimation; particle-based H-infinity filter scheme; sequential data fusion method; signal processing; statistical properties; Covariance matrix; Estimation; Filtering algorithms; Filtering theory; Mathematical model; Noise; Robustness; Monte Carlo method; data fusion; particle H¡Þ filter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent System Design and Engineering Application (ISDEA), 2012 Second International Conference on
  • Conference_Location
    Sanya, Hainan
  • Print_ISBN
    978-1-4577-2120-5
  • Type

    conf

  • DOI
    10.1109/ISdea.2012.479
  • Filename
    6173240