Accurate trajectory prediction is the cornerstone for future Air Traffic Management (ATM) concepts worldwide. To this purpose, researchers from Airservices Australia, the Federal Aviation Administration (FAA), and EUROCONTROL have collaborated on research into this important topic. Trajectory prediction is the process in which the future trajectory of an aircraft is computed based on a model of the aircraft's performance, forecast meteorological conditions and aircraft intent: a script that indicates how the aircraft is operated to fulfill the user-intentions of the flight while satisfying imposed constraints. The lateral component of the trajectory is mostly defined by the flight plan and if the plan is kept up to date, lateral uncertainty should be minimal. Longitudinally however, the problem is more complicated since not all required longitudinal aircraft intent is known to the ground-based Trajectory Predictor (TP). This paper presents the longitudinal performance of operational TPs from the FAA, EUROCONTROL, and Airservices Australia, which illustrates that inaccurate longitudinal aircraft intent and resulting excessive prediction errors are evident in all three TPs. The performance of the ground-based TPs was subsequently compared to data extracted from the aircraft's Flight Management System (FMS) through Future Air Navigation Systems (FANS) technology. FANS is standard equipment on wide-body aircraft and some domestic fleets, yet its full potential is widely under utilized. The paper argues significant improvement to ground based trajectory prediction accuracy is possible if the ground-TP is enhanced with aircraft data. It further demonstrates that this benefit can be achieved using aircraft data-link technologies, available today, to transmit FMS trajectory information.


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    Titel :

    Impact of missing longitudinal aircraft intent on descent trajectory prediction


    Beteiligte:


    Erscheinungsdatum :

    2011-10-01


    Format / Umfang :

    244344 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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