F. Jackman, Nearly Half of Commercial Jet Accidents Occur During Final Approach, Landing, 2014.

M. Tremaud, Getting To Grips With ALAR, tech. rep, 2000.

, 2036 Forecast Reveals Air Passengers Will Nearly Double to 7.8 Billion, 2017.

, Safety state program, DGAC, 2009.

, Safety state program, DGAC, 2013.

, Safety state program, horizon 2023, DGAC, 2019.

, Risk portfolio, DGAC, 2009.

A. Vernay, Defining a Compliant Approach (CA): A joint response to enhance the safety level of approach and landing, p.44, 2013.

M. Centro-de-publicaciones and . De-fomento, Accident Involving a Bombardier CL-600-2b19 (CRJ200), Registration EC-ITU, Operated by Air Nostrum, at the Barcelona Airport, on, tech. rep., Comisión de Investigación de Accidentes e Incidentes de Aviación Civil, 2011.

C. A. Hart, R. L. Sumwalt, M. R. Rosekind, and E. F. Weener, Descent Below Visual Glidepath and Impact With Seawall Asiana Airlines Flight 214 Boeing 777-200er, HL7742 San Francisco, California, National Transportation Safety Board, 2013.

J. Ramsay and B. Silverman, Functional Data Analysis, Second Edition, 2005.

J. O. Ramsay and B. W. Silverman, Applied Functional Data Analysis: Methods and Case Studies, 2007.

J. O. Ramsay, G. Hooker, and S. Graves, Functional Data Analysis with R and MATLAB, Use R!, 2009.

F. Ferraty and P. Vieu, Nonparametric Functional Data Analysis: Theory and Practice, Google-Books-ID: lMy6WPFZYFcC, 2006.

F. Ferraty, Recent Advances in Functional Data Analysis and Related Topics, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00794868

T. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer Series in Statistics, 2013.

S. Ullah and C. F. Finch, Applications of functional data analysis: A systematic review, BMC Medical Research Methodology, vol.13, 2013.

B. Gregorutti, Forêts Aléatoires et Sélection de Variables: Analyse Des Données Des Enregistreurs de Vol Pour La Sécurité Aérienne, 2015.

R. Suyundykov, S. Puechmorel, and L. Ferré, Multivariate Functional Data Clusterization by PCA in Sobolev Space Using Wavelets, 2010.
URL : https://hal.archives-ouvertes.fr/inria-00494702

C. Hurter, S. Puechmorel, F. Nicol, and A. Telea, Functional Decomposition for Bundled Simplification of Trail Sets, IEEE transactions on visualization and computer graphics, vol.24, issue.1, pp.500-510, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01587221

K. Tastambekov, Aircraft Trajectory Prediction by Local Functional Regression, 2012.

F. Nicol, Statistical Analysis of Aircraft Trajectories: a Functional Data Analysis Approach, The Third International Conference on Big Data, Small Data, Linked Data and Open Data, p.51, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01799104

C. Barreyre, B. Laurent, J. Loubes, B. Cabon, and L. Boussouf, Multiple testing for outlier detection in functional data, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01651191

C. Barreyre, B. Laurent, J. Loubes, B. Cabon, and L. Boussouf, Statistical Methods for Outlier Detection in Space Telemetries, p.2018

, SpaceOps Conference, (Marseille), 2018.

F. Yan, X. Lin, R. Li, and X. Huang, Functional principal components analysis on moving time windows of longitudinal data: dynamic prediction of times to event, Journal of the Royal Statistical Society: Series C (Applied Statistics), vol.67, pp.961-978, 2018.

I. Jolliffe, Principal component analysis, 2011.

J. Deville, Méthodes Statistiques et Numériques de l'analyse Harmonique, Annales de l'INSEE, pp.3-101, 1974.

J. Dauxois, Les Analyses Factorielles En Calcul Des Probabiblités et En Statistique: Essai d'étude Synthétique, 1976.

J. Dauxois, A. Pousse, and Y. Romain, Asymptotic Theory for the Principal Component Analysis of a Vector Random Function: Some Applications to Statistical Inference, Journal of multivariate analysis, vol.12, issue.1, pp.136-154, 1982.

V. Vapnik, The Nature of Statistical Learning Theory, 2013.

V. Vapnik, Adaptive and learning systems for signal processing, Statistical Learning Theory, 1998.

M. Ester, H. Kriegel, J. Sander, and X. Xu, A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise, Kdd, vol.96, issue.34, pp.226-231, 1996.

R. J. Campello, D. Moulavi, and J. Sander, Density-Based Clustering Based on Hierarchical Density Estimates, Advances in Knowledge Discovery and Data Mining, pp.160-172, 2013.

R. J. Campello, D. Moulavi, A. Zimek, and J. Sander, Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection, ACM Transactions on Knowledge Discovery from Data, vol.10, pp.1-51, 2015.

J. Perez and S. Fournie, Conception de procédures aux instruments -Cours IPD3f, tech. rep., École Nationale de L'Aviation Civile, 2017.

C. Lemozit, Aircraft Energy Management during Approach, 2005.

G. Jarry, D. Delahaye, and E. Féron, Trajectory approach analysis: A post-operational aircraft approach analysis tool, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02385671

G. Jarry, N. Couellan, and D. Delahaye, On the use of generative adversarial networks for aircraft trajectory generation and atypical approach detection, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02267170