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    CPHD filters with unknown quadratic clutter generators

    Access Status
    Fulltext not available
    Authors
    Mahler, Ronald
    Date
    2015
    Type
    Conference Paper
    
    Metadata
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    Citation
    Mahler, R. 2015. CPHD filters with unknown quadratic clutter generators.
    Source Title
    Proceedings of SPIE - The International Society for Optical Engineering
    DOI
    10.1117/12.2177177
    ISBN
    9781628415902
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/55686
    Collection
    • Curtin Research Publications
    Abstract

    © 2015 SPIE. Previous research has produced CPHD filters that can detect and track multiple targets in unknown, dynamically changing clutter. The.first such filters employed Poisson clutter generators and, as a result, were combinatorially complex. Recent research has shown that replacing the Poisson clutter generators with Bernoulli clutter generators results in computationally tractable CPHD filters. However, Bernoulli clutter generators are insufficiently complex to model real-world clutter with high accuracy, because they are statistically first-degree. This paper addresses the derivation and implementation of CPHD filters when first-degree Bernoulli clutter generators are replaced by second-degree quadratic clutter generators. Because these filters are combinatorially second-order, they are more easily approximated. They can also be implemented in exact closed form using beta-Gaussian mixture (BGM) or Dirichlet-Gaussian mixture (DGM) techniques.

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