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Improved Trajectory Prediction by Multi‐Aircraft Track Fusion for Air Traffic Control


I. Lymperopoulos

IfA Internal Seminar Series

Trajectory Prediction (TP) is a fundamental part of Air Traffic Control Operations. Constructing a method that reduces TP inaccuracies, we could both increase the capacity of the airspace by handling more aircraft and also retain high safety levels. Unfortunately, a main obstacle against the effort for increased accuracy is the uncertainty of weather forecasts, especially those that concern the wind. A remedy for this drawback is to exploit the known spatiotemporal correlation of wind prediction errors so as to create probabilistic weather maps for the present and the future. While this is possible and has been demonstrated to provide satisfactory results even for single aircraft, it is rightfully expected that acquiring information from multiple aircraft at different locations and time instances can lead to a more complete picture for a larger part of the airspace, thus improving even further the accuracy of TP. The challenge in this case is to handle the abundance of information efficiently, while dealing with the estimation of a high dimensional state. An additional complication is the non-linear dynamics of aircraft motion and control. We present an improved version of a Particle Filter algorithm that deals with these problems and provides efficient TP using only ground radar measurements. The algorithm exploits the structure of the problem to improve efficiency and eliminate the well known particle degeneracy problem, while successfully integrating information from multiple aircraft and increasing TP accuracy.


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