The Kalman Filter

Sharon Gannot, Arie Yeredor

    Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

    9 Scopus citations

    Abstract

    The Kalman filter and its variants are some of the most popular tools in statistical signal processing and estimation theory. In this chapter, we introduce the Kalman filter, providing a succinct, yet rigorous derivation thereof, which is based on the orthogonality principle. We also introduce several important variants of the Kalman filter, namely various Kalman smoothers, a Kalman predictor, a nonlinear extension (the extended Kalman filter), and adaptation to cases of temporally correlated measurement noise. The application of the Kalman filter to two important speech processing problems, namely, speech enhancement and speakerlocalization speaker localization is demonstrated.

    Original languageEnglish
    Title of host publicationSpringer Handbooks
    PublisherSpringer
    Pages135-160
    Number of pages26
    DOIs
    StatePublished - 2008

    Publication series

    NameSpringer Handbooks
    ISSN (Print)2522-8692
    ISSN (Electronic)2522-8706

    Bibliographical note

    Publisher Copyright:
    © 2008, Springer-Verlag Berlin Heidelberg.

    Keywords

    • Extend Kalman Filter
    • Kalman Filter
    • Mean Square Error
    • Speech Signal
    • Unscented Kalman Filter

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