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HYBRID DATA-DRIVEN AND PHYSICS-BASED FLIGHT TRAJECTORY PREDICTION IN TERMINAL AIRSPACE

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thesis
posted on 30.04.2021, 11:52 by Hansoo KimHansoo Kim
With the growing demand of air traffic, it becomes more important and critical than ever to develop advanced techniques to control and monitor air traffic in terms of safety and efficiency. Especially, trajectory prediction can play a significant role on the improvement of the safety and efficiency because predicted trajectory information is used for air traffic management such as conflict detection and resolution, sequencing and scheduling.
In this work, we propose a new framework by integrating
the two methods, called hybrid data-driven and physics-based trajectory prediction. The proposed algorithm is applied to real air traffic surveillance data to demonstrate its performance.

History

Degree Type

Master of Science

Department

Aeronautics and Astronautics

Campus location

West Lafayette

Advisor/Supervisor/Committee Chair

Inseok Hwang

Additional Committee Member 2

Martin Corless

Additional Committee Member 3

Dengfeng Sun

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