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Statistical prediction of aircraft trajectory : regression methods vs point-mass model

Ghasemi Hamed, Mohammad and Gianazza, David and Serrurier, Mathieu and Durand, Nicolas Statistical prediction of aircraft trajectory : regression methods vs point-mass model. (2013) In: 10th USA/Europe Air Traffic Management Research and Developpment Seminar (ATM 2013), 10 June 2013 - 13 June 2013 (Chicago, United States).

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Abstract

Ground-based aircraft trajectory prediction is a critical issue for air traffic management. A safe and efficient prediction is a prerequisite for the implementation of automated tools that detect and solve conflicts between trajectories. Moreover, regarding the safety constraints, it could be more reasonable to predict intervals rather than precise aircraft positions . In this paper, a standard point-mass model and statistical regression method is used to predict the altitude of climbing aircraft. In addition to the standard linear regression model, two common non-linear regression methods, neural networks and Loess are used. A dataset is extracted from two months of radar and meteorological recordings, and several potential explanatory variables are computed for every sampled climb segment. A Principal Component Analysis allows us to reduce the dimensionality of the problems, using only a subset of principal components as input to the regression methods. The prediction models are scored by performing a 10-fold cross-validation. Statistical regression results method appears promising. The experiment part shows that the proposed regression models are much more efficient than the standard point-mass model. The prediction intervals obtained by our methods have the advantage of being more reliable and narrower than those found by point-mass model.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to ATM editor. The definitive version is available at http://www.atmseminar.org The original PDF is available at: http://www.atmseminar.org/seminarContent/seminar10/papers/350-Hamed_0125130314-Final-Paper-4-9-13.pdf
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Ecole Nationale de l'Aviation Civile - ENAC (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Laboratory name:
Statistics:download
Deposited By: IRIT IRIT
Deposited On:10 Nov 2015 09:21

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