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    Divergence detectors for multitarget tracking algorithms

    Access Status
    Fulltext not available
    Authors
    Mahler, Ronald
    Date
    2013
    Type
    Conference Paper
    
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    Citation
    Mahler, R. 2013. Divergence detectors for multitarget tracking algorithms.
    Source Title
    Proceedings of SPIE - The International Society for Optical Engineering
    DOI
    10.1117/12.2015450
    ISBN
    9780819495365
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/55142
    Collection
    • Curtin Research Publications
    Abstract

    Single-target tracking filters will typically diverge when their internal measurement or motion models deviate too much from the actual models. Niu, Varshney, Alford, Bubalo, Jones, and Scalzo have proposed a metric- the normalized innovation squared (NIS)-that recursively estimates the degree of nonlinearity in a single-target tracking problem by detecting filter divergence. This paper establishes the following: (1) NIS can be extended to generalized NIS (GNIS), which addresses more general nonlinearities; (2) NIS and GNIS are actually anomaly detectors, rather than filter-divergence detectors; (3) NIS can be heuristically generalized to a multitarget NIS (MNIS) metric; (4) GNIS also can be rigorously extended to multitarget problems via the multitarget GNIS (MGNIS); (5) explicit, computationally tractable formulas for MGNIS can be derived for use with CPHD and PHD filters; and thus (6) these formulas can be employed as anomaly detectors for use with these filters. © 2013 SPIE.

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