In this paper, a trajectory anomaly detection method for aircraft in terminal airspace surrounding an airport is proposed. This method, as an effective and efficient way for anomaly detection, assists aircraft condition monitoring system (ACMS) for safety analysis. Considering the characteristics of aircraft, a trajectory reconstruction method based on ADS-B data is presented. Then, the mixture density network is utilized to extract the standard trend. Furthermore, accurate inferences about trajectories are made. Finally, the trajectories are classified as either normal or abnormal based on the probability assessment method. Extensive tests on real flight data show that proposed models performs well in anomaly detection and are suitable for expanding flight data.


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    Titel :

    A Novel Anomaly Detection Method for Aircraft Trajectory in Terminal Airspace


    Beteiligte:
    Chen, Li-Jing (Autor:in) / Zeng, Wei-Li (Autor:in) / Xu, Zheng-Feng (Autor:in) / Yang, Ai-Wen (Autor:in) / Yang, Zhao (Autor:in)

    Kongress:

    20th COTA International Conference of Transportation Professionals ; 2020 ; Xi’an, China (Conference Cancelled)


    Erschienen in:

    CICTP 2020 ; 3181-3193


    Erscheinungsdatum :

    09.12.2020




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch