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Advanced statistical signal processing for next generation trajectory prediction

Author
Khaledian, H.; Prats, X.; Jordi , V.
Type of activity
Presentation of work at congresses
Name of edition
International Conference on Research in Air Transportation
Date of publication
2020
Presentation's date
2020-06-23
Book of congress proceedings
Proceedings of 9th ICRAT 2020 - International Conference on Research in Air Transportation
Project funding
PhD studentship with the support of the SESAR Engage Knowledge Transfer Network
Repository
http://hdl.handle.net/2117/328697 Open in new window
URL
http://www.icrat.org/icrat/upcoming-conference/papers/ Open in new window
Abstract
Trajectory Prediction (TP) is fundamental in Air Traffic Management (ATM). This research focuses on TP for the execution phase of the flight. In contrast to exploit black-box machine learning-based solutions, we tackle TP as an estimation problem, resorting to mathematical tools arising from statistical signal processing. Our first goal is to find an optimal and robust 4D (3D space plus time) TP solution, and the real-time estimation of the aircraft's active guidance mode, observing flight data ...
Citation
Khaledian, H.; Prats, X.; Jordi, V. Advanced statistical signal processing for next generation trajectory prediction. A: International Conference on Research in Air Transportation. "Proceedings of 9th ICRAT 2020 - International Conference on Research in Air Transportation". 2020,
Keywords
4D-TP, ADSB and Mode S data., Guidance Mode Identification, Robustness, Statistical Signal Processing, Trajectory Prediction
Group of research
ICARUS - Intelligent Communications and Avionics for Robust Unmanned Aerial Systems

Participants