Aircraft climb trajectories are difficult to predict, and large errors in these predictions reduce the potential operational benefits of some advanced features for NextGen. The algorithm described in this paper improves climb trajectory prediction accuracy by adjusting trajectory predictions based on observed track data. It utilizes rate-of-climb and airspeed measurements derived from position data to dynamically adjust the aircraft weight modeled for trajectory predictions. In simulations with weight uncertainty, the algorithm is able to adapt to within 3 percent of the actual gross weight within two minutes of the initial adaptation. The root-mean-square of altitude errors for five-minute predictions was reduced by 73 percent. Conflict detection performance also improved, with a 15 percent reduction in missed alerts and a 10 percent reduction in false alerts. In a simulation with climb speed capture intent and weight uncertainty, the algorithm improved climb trajectory prediction accuracy by up to 30 percent and conflict detection performance, reducing missed and false alerts by up to 10 percent.


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    Title :

    Adaptive Trajectory Prediction Algorithm for Climbing Flights



    Conference:

    AIAA Guidence, Navigation, and Control Conference ; 2012 ; Minneapolis, MN, United States


    Publication date :

    2012-08-13


    Type of media :

    Conference paper


    Type of material :

    No indication


    Language :

    English




    Adaptive Trajectory Prediction Algorithm for Climbing Flights

    Schultz, Charles / Thipphavong, David / Erzberger, Heinz | AIAA | 2012


    Adaptive Trajectory Prediction Algorithm for Climbing Flights

    Schultz, C. / Thipphavong, D. / Erzberger, H. et al. | British Library Conference Proceedings | 2012


    THE EFFECT OF RATE-OF-CLIMB UNCERTAINTY ON AN ADAPTIVE TRAJECTORY PREDICTION ALGORITHM FOR CLIMBING FLIGHTS

    Thipphavong, D. / Schultz, C. / American Institute of Aeronautics and Astronautics; International Society for Structural and Multidisciplinary Optimization | British Library Conference Proceedings | 2012