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    A generalized labeled multi-bernoulli filter with object spawning

    Access Status
    Fulltext not available
    Authors
    Bryant, D.
    Vo, Ba Tuong
    Vo, Ba-Ngu
    Jones, B.
    Date
    2018
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Bryant, D. and Vo, B.T. and Vo, B. and Jones, B. 2018. A generalized labeled multi-bernoulli filter with object spawning. IEEE Transactions on Signal Processing. 66 (23): pp. 6177-6189.
    Source Title
    IEEE Transactions on Signal Processing
    DOI
    10.1109/TSP.2018.2872856
    ISSN
    1053-587X
    School
    School of Electrical Engineering, Computing and Mathematical Science (EECMS)
    Funding and Sponsorship
    http://purl.org/au-research/grants/arc/DP170104854
    http://purl.org/au-research/grants/arc/DP160104662
    URI
    http://hdl.handle.net/20.500.11937/72442
    Collection
    • Curtin Research Publications
    Abstract

    Previous labeled random finite set filter developments use a motion model that only accounts for survival and birth. While such a model provides the means for a multi-object tracking filter, such as the generalized labeled multi-Bernoulli (GLMB) filter to capture object births and deaths in a wide variety of applications, it lacks the capability to capture spawned tracks and their lineages. In this paper, we propose a new Generalized Labeled Multi-Bernoulli (GLMB)-based filter that formally incorporates spawning, in addition to birth. This formulation enables the joint estimation of a spawned object's state and information regarding its lineage. Simulations results demonstrate the efficacy of the proposed formulation.

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