• DocumentCode
    2080799
  • Title

    Nonlinear filtering with small observation noise

  • Author

    Ji, Dunmu

  • Author_Institution
    Div. of Appl. Math., Brown Univ., Providence, RI, USA
  • fYear
    1989
  • fDate
    13-15 Dec 1989
  • Firstpage
    2572
  • Abstract
    A study is made of the nonlinear filtering of diffusions when the observation noise covariance is proportional to ε2, a small parameter. It is shown that the suboptimal solution obtained by the extended Kalman filter is an approximation in the L2 sense of order ε2 to the best nonlinear filter. The technique involves the use of an efficient linearization method obtained via the Girsanov transformation
  • Keywords
    diffusion; filtering and prediction theory; linearisation techniques; Girsanov transformation; diffusions; extended Kalman filter; linearization method; nonlinear filtering; observation noise covariance; Computer errors; Eigenvalues and eigenfunctions; Error analysis; Filtering; Filters; Gaussian processes; Mathematics; Probability; Tellurium; Tiles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1989., Proceedings of the 28th IEEE Conference on
  • Conference_Location
    Tampa, FL
  • Type

    conf

  • DOI
    10.1109/CDC.1989.70642
  • Filename
    70642
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2080799