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    Kalman filtering with faded measurements

    Dey, Subhrakanti and Leong, Alex S. and Evans, Jamie S. (2009) Kalman filtering with faded measurements. Automatica, 45 (10). ISSN 0005-1098

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    This paper considers a sensor network where single or multiple sensors amplify and forward their measurements of a common linear dynamical system (analog uncoded transmission) to a remote fusion center via noisy fading wireless channels. We show that the expected error covariance (with respect to the fading process) of the time-varying Kalman filter is bounded and converges to a steady state value, based on some earlier results on asymptotic stability of Kalman filters with random parameters. More importantly, we provide explicit expressions for sequences which can be used as upper bounds on the expected error covariance, for specific instances of fading distributions and scalar measurements (per sensor). Numerical results illustrate the effectiveness of these bounds.

    Item Type: Article
    Keywords: Fading channels; Kalman filtering; Sensor networks; Stability;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 14421
    Identification Number:
    Depositing User: Subhrakanti Dey
    Date Deposited: 11 May 2021 14:32
    Journal or Publication Title: Automatica
    Publisher: Elsevier
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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