Two maneuvering-target tracking techniques are compared. The first, called input estimation, models the maneuver as constant unknown input, estimates its magnitude and onset time, and then corrects the state estimate accordingly. The second models the maneuver as a switching of the target state model, where the various state models can be of different dimension and driven by process noises of different intensities, and estimates the state according to the interacting multiple model (IMM) algorithm. While the first requires around twenty parallel filters, it is shown that the latter, implemented in the form of the IMM, performs equally well or better with two or three filters.<>


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    Title :

    Tracking a maneuvering target using input estimation versus the interacting multiple model algorithm


    Contributors:
    Bar-Shalom, Y. (author) / Chang, K.C. (author) / Blom, H.A.P. (author)


    Publication date :

    1989-03-01


    Size :

    374946 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English