Data fusion for multiple surveillance sensors in air traffic control (ATC) is studied. The goal is to build up software redundancy for better target tracking accuracy and robustness against sensor faults. A set of hybrid estimation algorithms for different sensors is designed to run in parallel for tracking aircraft with changing flight modes. The proposed sensor fusion algorithm combines the estimates from each hybrid estimation algorithm and identifies potential sensor faults.


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    Title :

    Multi-Sensor Fusion and Fault Detection using Hybrid Estimation for Air Traffic Surveillance


    Contributors:
    Weiyi Liu (author) / Jian Wei (author) / Mengchen Liang (author) / Yi Cao (author) / Inseok Hwang (author)


    Publication date :

    2013-10-01


    Size :

    2880184 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English