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    Error Bounds for Joint Detection and Estimation of a Single Object With Random Finite Set Observation

    Access Status
    Fulltext not available
    Authors
    Rezaeian, M.
    Vo, Ba-Ngu
    Date
    2010
    Type
    Journal Article
    
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    Citation
    Rezaeian, M. and Vo, B. 2010. Error Bounds for Joint Detection and Estimation of a Single Object With Random Finite Set Observation. IEEE Transactions on Signal Processing. 58 (3): pp. 1493-1506.
    Source Title
    IEEE Transactions on Signal Processing
    DOI
    10.1109/TSP.2009.2037665
    ISSN
    1053-587X
    URI
    http://hdl.handle.net/20.500.11937/41587
    Collection
    • Curtin Research Publications
    Abstract

    This paper considers the performance limits for joint detection and estimation from a finite set-valued observation that is stochastically related to the state or parameter of interest. Detection refers to inference about the existence of the state, whereas estimation refers to inference about its value, when detected. Since we need to determine the existence/non-existence of the state as well as its value, the usual notion of Euclidean distance error does not jointly capture detection and estimation error in a meaningful manner. Treating the state as set, which can be either empty or singleton, admits a meaningful distance error for joint detection and estimation. We derive bounds on this distance error for a widely used class of observation models. When existence of the state is a certainty, our bounds coincide with recent results on Cramer-Rao bounds for estimation only problems.

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