• DocumentCode
    336678
  • Title

    Non-linear state estimation by Monte Carlo filters: a six-dimensional example

  • Author

    Bolviken, E. ; Christophersen, Nils

  • Author_Institution
    Inst. of Math., Oslo Univ., Norway
  • Volume
    3
  • fYear
    1998
  • fDate
    1998
  • Firstpage
    2892
  • Abstract
    We present a general Monte Carlo-based algorithm for computing Bayesian estimates in non-linear state space models, and apply it to bearings-only target tracking. The parameters of the measurement noise are determined online as part of the state estimation. The state vector then becomes six-dimensional, but the problem is still handled in real time
  • Keywords
    Bayes methods; Monte Carlo methods; adaptive estimation; filtering theory; state estimation; state-space methods; target tracking; Bayesian estimates; Monte Carlo filters; bearings-only target tracking; measurement noise; nonlinear state estimation; nonlinear state space models; six-dimensional state vector; Bayesian methods; Covariance matrix; Filters; Monte Carlo methods; Noise generators; Sampling methods; State estimation; State-space methods; Target tracking; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1998. Proceedings of the 37th IEEE Conference on
  • Conference_Location
    Tampa, FL
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-4394-8
  • Type

    conf

  • DOI
    10.1109/CDC.1998.757915
  • Filename
    757915
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=336678