State and information space estimation: A comparison

Arthur G.O. Mutambara, Marwan S.Y. Al-Haik

Research output: Contribution to journalConference articlepeer-review

6 Citations (Scopus)


In this paper state and information space estimation methods used in both linear and nonlinear systems are compared. The (linear) information filter is introduced as an algebraic equivalent to the Kalman filter. Linear information space is extended to nonlinear information space by outlining the extended information filter. The algebraic equivalence of this filter to the extended Kalman filter and the benefits of nonlinear information space are illustrated by considering a system involving both nonlinear state evolution and nonlinear observations.

Original languageEnglish
Pages (from-to)2374-2375
Number of pages2
JournalProceedings of the American Control Conference
Publication statusPublished - 1997
Externally publishedYes
EventProceedings of the 1997 American Control Conference. Part 3 (of 6) - Albuquerque, NM, USA
Duration: 4 Jun 19976 Jun 1997

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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