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    Multitarget tracking using sensors with known correlations

    Access Status
    Fulltext not available
    Authors
    Mahler, Ronald
    Date
    2016
    Type
    Conference Paper
    
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    Citation
    Mahler, R. 2016. Multitarget tracking using sensors with known correlations.
    Source Title
    Proceedings of SPIE - The International Society for Optical Engineering
    DOI
    10.1117/12.2224112
    ISBN
    9781510600836
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/56380
    Collection
    • Curtin Research Publications
    Abstract

    © 2016 SPIE. This paper is the fourth in a series aimed at weakening the independence assumptions that are typically presumed in multitarget tracking. Specifically, we assume that, in a multisensory scenario, the sensors are not necessarily independent but, rather, have known correlations (i.e., their joint single-target joint likelihood function is known). From this, we construct a multitarget measurement model for sensors with known correlations. From this model we derive, as an illustrative example, the filtering equations for a probability hypothesis density (PHD) filter for sensors with known correlations. We emphasize the two-sensor case of this filter, for which the measurement-update equations involve a summation over all measurement-to-measurement associations between the two sensors.

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