• DocumentCode
    184740
  • Title

    The continuous-discrete time feedback particle filter

  • Author

    Tao Yang ; Blom, Henk A. P. ; Mehta, Prashant G.

  • Author_Institution
    Coordinated Sci. Lab., Univ. of Illinois at Urbana-Champaign (UIUC), Urbana, IL, USA
  • fYear
    2014
  • fDate
    4-6 June 2014
  • Firstpage
    648
  • Lastpage
    653
  • Abstract
    In this paper, the feedback particle filter (FPF) algorithm is introduced for the continuous-discrete time nonlinear filtering problem. As with the continuous-time FPF, the continuous-discrete time algorithm i) admits an innovation error-based feedback control structure, and ii) requires a solution of an Euler-Lagrange boundary value problem (E-L BVP). These solutions are described in closed-form for the linear Gaussian filtering problem. For the general nonlinear non-Gaussian case, an algorithm is described to obtain an approximate solution of the E-L BVP. Comparisons are also made to the particle flow filter algorithm introduced by Daum and Huang.
  • Keywords
    boundary-value problems; continuous time filters; discrete time filters; feedback; particle filtering (numerical methods); E-L BVP; Euler-Lagrange boundary value problem; continuous-discrete time algorithm; continuous-discrete time feedback particle filter; continuous-discrete time nonlinear filtering problem; continuous-time FPF algorithm; innovation error-based feedback control structure; linear Gaussian filtering problem; nonlinear nonGaussian case; particle flow filter algorithm; Approximation algorithms; Equations; Feedback control; Kalman filters; Mathematical model; Silicon; Standards; Estimation; Filtering; Kalman filtering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2014
  • Conference_Location
    Portland, OR
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-3272-6
  • Type

    conf

  • DOI
    10.1109/ACC.2014.6859259
  • Filename
    6859259