Climb Trajectory Prediction Enhancement Using Airline Flight-planning Information

Software decision support tools that assist controllers with the management of air traffic are dependent upon the ability to accurately predict future aircraft positions. Trajectory predictions in en route airspace rely upon the availability of aircraft state, aircraft performance, pilot intent, and atmospheric data. The use of real-time airline information for improving ground-based trajectory predictions has been a recent focus in the development of the Center-TRACON Automation System (CTAS) at NASA Ames. This paper studies the impact of airline flight-planning data on CTAS en route climb trajectory prediction accuracy. The climb trajectory synthesis process is first described along with existing input data. Flight–planning data parameters, available from a typical airline operations center, are then discussed along with their potential usefulness to CTAS. Results are then presented to show the significant impact of airline-provided takeoff weight, speed-profile, and thrust calibration data on CTAS climb trajectory prediction performance.