The surveillance data obtained from an unmanned aerial vehicle during real-time operation are very important for unmanned aerial vehicle supervision. In this study, in order to obtain more reliable and accurate unmanned aerial vehicle flight paths, we have proposed a trajectory fusion method of unmanned aerial vehicle data based on an active and passive feedback system. The active surveillance data are obtained from automatic dependent surveillance – broadcast and the passive surveillance data are derived from the unmanned aerial vehicle ground control station. The convex combination fusion algorithm is employed to fuse the two sets of data to obtain the accurate flight state and a continuous stable running track for the unmanned aerial vehicle. The simulation results showed that the fusion trajectory obtained using the convex combination fusion algorithm was smoother than the local trajectory obtained by the interacting multiple model algorithm.


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    Title :

    Unmanned aerial vehicle trajectory data fusion based on an active and passive feedback system


    Contributors:
    Tang, Xin-min (author) / Chen, Ji-da (author) / Li, Teng (author)


    Publication date :

    2020-03-01


    Size :

    9 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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