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    Tracking spawning objects

    Access Status
    Fulltext not available
    Authors
    Mahler, Ronald
    Maroulas, V.
    Date
    2013
    Type
    Journal Article
    
    Metadata
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    Citation
    Mahler, R. and Maroulas, V. 2013. Tracking spawning objects. IET Radar, Sonar and Navigation. 7 (3): pp. 321-331.
    Source Title
    IET Radar, Sonar and Navigation
    DOI
    10.1049/iet-rsn.2012.0053
    ISSN
    1751-8784
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/56326
    Collection
    • Curtin Research Publications
    Abstract

    Many multi-object tracking scenarios are complicated by the fact that an object of interest may spawn additional objects which, for some period of time, follow roughly the same trajectory as the original object and then fall away. The challenge is then to discriminate the original object from the spawned ancillaries in a timely fashion. This study proposes a solution to this problem based on the increasingly well-known multi-object track-before-detect algorithm called the cardinalised probability hypothesis density (CPHD) filter. Precisely, the authors assume zero false alarms (ZFA) in the CPHD filter, and apply the proposed scheme to linear and non-linear simulation scenarios based on widely used object-trajectory and sensor models. The authors have also demonstrated that a Gaussian mixture implementation of the ZFA-CPHD filter (i) establishes stable estimates of object number, (ii) rapidly eliminates the ancillary objects and (iii) detects and accurately estimates the trajectory of the original object of interest.

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