A novel approach to tracking a maneuvering target is developed. This approach does not rely on a statistical description of the maneuver as a random process. Instead, the state model for the target is changed by introducing extra state components when a maneuver is detected. The maneuver, modeled as an acceleration, is estimated recursively. The performance of this estimator is shown to be superior to a recent algorithm presented by Chan et al. that handles the maneuver by estimating it as an unknown input. A significant departure from the current practice of comparison of algorithms is made: a recently introduced rigorous statistical methodology is used in the comparison of these estimators.


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    Titel :

    Variable Dimension Filter for Maneuvering Target Tracking


    Beteiligte:
    Bar-Shalom, Y. (Autor:in) / Birmiwal, K. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.09.1982


    Format / Umfang :

    2177083 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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