Date - Heure / Date - Hour
Date(s) - 25/01/2018
11h00 - 12h00
Emplacement / Location
ENAC, Building Breguet, Amphi Breguet
Detection of bad runway conditions using radar landing tracks.
In air transportation, a huge amount of data is continuously recorded such as radar tracks that may be used for improving flight as well as airport safety. However, all known statistical algorithms, even those based on functional data, are unable to distinguish between a safety critical flight and another one departing from standard behavior, but otherwise safe. It is the case in airport safety when radar measurements are used for detecting incidents on airport surface.
We propose a change of paradigm by switching from a functional data framework to a geometrical one by representing curves as points in a shape manifold. In this way, any intrinsic structure of the data that is amenable to geometry can be directly encoded in the representation space. Based on an extension of a classical distance between shapes, a new one is defined, that explicitly takes into account the second derivative and can be related to slippery. The basics on functional data analysis are introduced in a first part, then some results on datasets of synthetic and real trajectories are presented.
This talk is an introduction to the workshop DOFINn that wil take place Friday 26th January 2018 at Enac. It is part of the IENAC Big Data courses.
Florence Nicol, DEVI research team, ENAC.