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Real-time Identification of Guidance Modes in Aircraft Descents Using Surveillace Data
Dalmau Codina, Ramon; Pérez Batlle, Marcos; Prats Menéndez, Xavier
Universitat Politècnica de Catalunya. Departament de Física; Universitat Politècnica de Catalunya. ICARUS - Intelligent Communications and Avionics for Robust Unmanned Aerial Systems
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37th DASC Best student paper award,2018; premi al millor article de la conferència on el primer autor és un estudiant, atorgat per l'Institute of Electrical and Electronics Engineers
Trajectory predictors require information on the flight-intent in order to estimate the future state of the aircraft. At present, however, such information is not available or it is very limited and coarse (unless predicting the ownship trajectory). In this paper, an interacting multiple-model (IMM) algorithm is proposed to improve the accuracy of short-term trajectory predictions. The active guidance mode of an aircraft is estimated in real-time observing flight data collected only from automatic dependent surveillance-Broadcast (ADS-B) and transponder selective mode (Mode S) emissions. The algorithm is set up with different models corresponding to the most typical guidance modes, and provides the model that better fits the observations. The proposed algorithm is validated by means of two simulated trajectories whose guidance modes were known beforehand. Finally, the performance of the algorithm with real flight data is demonstrated through a detailed example. Promising results are obtained, showing that the active guidance mode can be unequivocally identified with a negligible delay.
Peer Reviewed
Award-winning
-Àrees temàtiques de la UPC::Aeronàutica i espai
-Navigation (Aeronautics)
-Air traffic control
-Trànsit aeri -- Control
-Navegació aèria -- Control
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Article - Published version
Conference Object
Institute of Electrical and Electronics Engineers (IEEE)
         

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