Real-time Identification of Guidance Modes in Aircraft Descents Using Surveillace Data
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
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.
© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.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
CitationDalmau, R.; Perez-Batlle, M.; Prats, X. Real-time Identification of Guidance Modes in Aircraft Descents Using Surveillace Data. A: Digital Avionics Systems Conference. "37th DASC Digital Avionics Systems Conference: London, England, UK, September 23-27, 2018: 2018 conference proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1-10.