A Tool for Kalman Filter Tuning

Publication: ResearchArticle in proceedings – Annual report year: 2007

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The Kalman filter requires knowledge about the noise statistics. In practical applications, however, the noise covariances are generally not known. A method for estimating noise covariances from process data has been investigated. The method gives a least-squares estimate of the noise covariances, which can be used to compute the Kalman filter gain.
Original languageEnglish
Title of host publication17th European Symposium on Computer Aided Process Engineering - ESCAPE17, 2007
Number of pages1392
VolumeVolume 24
PublisherElsevier
Publication date2007
Pages859-864
ISBN (print)978-0-444-53157-5
DOIs
StatePublished

Conference

Conference17th European Symposium on Computer Aided Process Engineering
Number17
CountryRomania
CityBucharest
Period27/05/0730/05/07
SponsorUniv Bucharest; Univ Cluj Napoca
Internet addresshttp://www.escape17.upb.ro/index.htm
NameComputer Aided Chemical Engineering
CitationsWeb of Science® Times Cited: No match on DOI

Keywords

  • Covariance Estimation, State estimation, Kalman filter
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