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

Daniel Sigalov, Tomer Michaeli, Yaakov Oshman

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number6748893
Pages (from-to)2549-2554
Number of pages6
JournalIEEE Transactions on Automatic Control
Volume59
Issue number9
DOIs
StatePublished - Sep 2014

Keywords

  • Clutter and data association
  • state estimation
  • target tracking

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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