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    A recursive linear MMSE filter for dynamic systems with unknown state vector means

    200783_200783.pdf (236.6Kb)
    Access Status
    Open access
    Authors
    Khodabandeh, A.
    Teunissen, Peter
    Date
    2014
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Khodabandeh, A. and Teunissen, P. 2014. A recursive linear MMSE filter for dynamic systems with unknown state vector means. International Journal on Geomathematics. 5 (1): pp. 17-31.
    Source Title
    International Journal on Geomathematics
    DOI
    10.1007/s13137-014-0058-0
    ISSN
    1869-2672
    School
    Department of Spatial Sciences
    Remarks

    The final publication is available at Springer via http://doi.org/10.1007/s13137-014-0058-0

    URI
    http://hdl.handle.net/20.500.11937/35782
    Collection
    • Curtin Research Publications
    Abstract

    In this contribution we extend Kalman-filter theory by introducing a new recursive linear minimum mean squared error (MMSE) filter for dynamic systems with unknown state-vector means. The recursive filter enables the joint MMSE prediction and estimation of the random state vectors and their unknown means, respectively. We show how the new filter reduces to the Kalman-filter in case the state-vector means are known and we discuss the fundamentally different roles played by the initialization of the two filters.

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