A highly adaptable and extensible method for predicting four-dimensional trajectories of civil aircraft has been developed. This method, Behavior-Based Trajectory Prediction, is based on taxonomic concepts developed for the description and comparison of trajectory prediction software. A hierarchical approach to the "behavioral" layer of a point-mass model of aircraft flight, a clear separation between the "behavioral" and "mathematical" layers of the model, and an abstraction of the methods of integrating differential equations in the "mathematical" layer have been demonstrated to support aircraft models of different types (in particular, turbojet vs. turboprop aircraft) using performance models at different levels of detail and in different formats, and promise to be easily extensible to other aircraft types and sources of data. The resulting trajectories predict location, altitude, lateral and vertical speeds, and fuel consumption along the flight path of the subject aircraft accurately and quickly, accounting for local conditions of wind and outside air temperature. The Behavior-Based Trajectory Prediction concept was implemented in NASA's Traffic Aware Planner (TAP) flight-optimizing cockpit software application.


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    Titel :

    Point-Mass Aircraft Trajectory Prediction Using a Hierarchical, Highly-Adaptable Software Design


    Beteiligte:
    D. A. Karr (Autor:in) / R. A. Vivona (Autor:in) / S. E. Woods (Autor:in) / D. J. Wing (Autor:in)

    Erscheinungsdatum :

    2017


    Format / Umfang :

    12 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch




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