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    Particle filter for extracting target label information when targets move in close proximity

    Access Status
    Fulltext not available
    Authors
    Garcia Fernandez, Angel
    Morelande, M.
    Grajal, J.
    Date
    2011
    Type
    Conference Paper
    
    Metadata
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    Citation
    Garcia Fernandez, A. and Morelande, M. and Grajal, J. 2011. Particle filter for extracting target label information when targets move in close proximity.
    Source Title
    Fusion 2011 - 14th International Conference on Information Fusion
    ISBN
    9781457702679
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/53912
    Collection
    • Curtin Research Publications
    Abstract

    This paper addresses the problem of approximating the posterior probability density function of two targets after a crossing from the Bayesian perspective such that the information about target labels is not lost. To this end, we develop a particle filter that is able to maintain the inherent multimodality of the posterior after the targets have moved in close proximity. Having this approximation available, we are able to extract information about target labels even when the measurements do not provide information about target's identities. In addition, due to the structure of our particle filer, we are able to use an estimator that provides lower optimal subpattern assignment (OSPA) errors than usual estimators. © 2011 IEEE.

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