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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Variable Dimension Filter for Maneuvering Target Tracking


    Contributors:

    Published in:

    Publication date :

    1982-09-01


    Size :

    2177083 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Enhanced variable dimension filter for maneuvering target tracking

    Cloutier, J.R. / Lin, C.-F. / Yang, C. | IEEE | 1993




    Maneuvering target tracking using extended Kalman filter

    Cortina, E. / Otero, D. / D'Attellis, C.E. | IEEE | 1991