Tracking a maneuvering target in a nonlinear interference environment has been discussed in some literature, and this paper considers the problems of tracking in the non-Gaussian noise environment and then tracking with multiple passive sensors. The method of target state estimation in this paper is a dynamic programming approach. Unlike the traditional method, the estimating problem is reduced to a multiple hypothesis-testing problem, and then is solved by using the dynamic programming algorithm. The simulation results show the superiority of the new method to EKF.


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    Title :

    Maneuvering target tracking with non-Gaussian noise


    Contributors:


    Publication date :

    1997-01-01


    Size :

    451651 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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