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    Bayesian unified registration and tracking

    Access Status
    Fulltext not available
    Authors
    Mahler, Ronald
    El-Fallah, A.
    Date
    2011
    Type
    Conference Paper
    
    Metadata
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    Citation
    Mahler, R. and El-Fallah, A. 2011. Bayesian unified registration and tracking.
    Source Title
    Proceedings of SPIE - The International Society for Optical Engineering
    DOI
    10.1117/12.885145
    ISBN
    9780819486240
    School
    Department of Electrical and Computer Engineering
    URI
    http://hdl.handle.net/20.500.11937/55826
    Collection
    • Curtin Research Publications
    Abstract

    Multitarget detection and tracking algorithms typically presume that sensors are spatially registered - i.e., that all sensor states are precisely specified with respect to some common coordinate system. In actuality, sensor observations may be contaminated by unknown spatial misregistration biases. This paper demonstrates that these biases can be estimated by exploiting the data collected from a sufficiently large number of unknown targets, in a unified methodology in which sensor registration and multitarget tracking are performed jointly in a fully unified fashion. We show how to (1) model single-sensor bias, (2) integrate the biased sensors into a single probabilistic multiplatform-multisensor-multitarget system, (3) construct the optimal solution to the joint registration/tracking problem, and (4) devise a principled computational approximation of this optimal solution. The approach does not presume the availability of GPS or other inertial information. © 2011 SPIE.

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