• DocumentCode
    5924
  • Title

    LMMSE Filtering in Feedback Systems With White Random Modes: Application to Tracking in Clutter

  • Author

    Sigalov, Daniel ; Michaeli, Tomer ; Oshman, Yaakov

  • Author_Institution
    Dept. of Math., Technion - Israel Inst. of Technol., Haifa, Israel
  • Volume
    59
  • Issue
    9
  • fYear
    2014
  • fDate
    Sept. 2014
  • Firstpage
    2549
  • Lastpage
    2554
  • Abstract
    A generalized state space representation of dynamical systems with random modes switching according to a white random process is presented. The new formulation includes a term, in the dynamics equation, that depends on the most recent linear minimum mean squared error (LMMSE) estimate of the state. This can model the behavior of a feedback control system featuring a state estimator. The measurement equation is allowed to depend on the previous LMMSE estimate of the state, which can represent the fact that measurements are obtained from a validation window centered about the predicted measurement and not from the entire surveillance region. The LMMSE filter is derived for the considered problem. The approach is demonstrated in the context of target tracking in clutter and is shown to be competitive with several popular nonlinear methods.
  • Keywords
    feedback; state estimation; state-space methods; LMMSE filtering; dynamical systems; feedback control system; feedback systems; generalized state space representation; linear minimum mean squared error; measurement equation; nonlinear methods; random mode switching; state estimation; target tracking context; validation window; white random modes; Clutter; Equations; Estimation; Mathematical model; Switches; Target tracking; Time measurement; Clutter and data association; state estimation; target tracking;
  • fLanguage
    English
  • Journal_Title
    Automatic Control, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9286
  • Type

    jour

  • DOI
    10.1109/TAC.2014.2308601
  • Filename
    6748893