State Matrix Kalman Filter

Daniel Choukroun, Itzhack Y. Bar-Itzhack, Haim Weiss, Yaakov Oshman

Research output: Contribution to journalConference articlepeer-review

7 Scopus citations


The paper presents a general discrete-time Kalman filter for state matrix estimation using matrix measurements. The new algorithm evaluates the state matrix estimate and the estimation error covariance matrix in terms of the original system matrices. The proposed algorithm naturally fits systems which are most conveniently described by matrix process and measurement equations. Its formulation uses a compact notation for aiding both intuition and mathematical manipulation. It is a straightforward extension of the classical Kalman filter, and includes as special cases other matrix filters that were developed in the past.

Original languageEnglish
Pages (from-to)393-398
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
StatePublished - 1 Dec 2003
Externally publishedYes
Event42nd IEEE Conference on Decision and Control - Maui, HI, United States
Duration: 9 Dec 200312 Dec 2003

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization


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