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Archiv-Übersicht     Angebot Nr. 13734

Angebotsdatum: 16. Dezember 2019
Art der Stelle: Doktorarbeit / Diplomarbeit
Fachgebiet: Physik > Angewandte Physik
Titel des Themas: Detection of wake vortices in LIDAR - measurements using artificial neural networks

Institut: Institut für Physik der Atmosphäre
Dr. rer. nat. Anton Stephan
Münchener Str. 20
82234 Weßling
Tel.:    Fax.:
Bundesland: Bayern
Homepage: http://https://www.dlr.de/dlr/jobs/en/desktopdefault.aspx/tabid-10596/1003_read-40104/
E-Mail Kontakt: mail

Beschreibung: Flying aircraft generate a pair of co-rotating vortices, the so-called wake vortices. In the final approach, wake vortices can endanger following aircraft; they continue to be the main cause of existing aircraft separation at airports. Monitoring wake vortices at airports is complex both in terms of the instruments used and the processing. In recent years, LIDAR (Light Detection And Ranging) has established itself as a suitable instrument for measuring the aircraft wake flow. However, good evaluation algorithms of the LIDAR signal are very time-consuming, so that an operational application at airports for real-time observation is out of the question.

Thanks to the current developments in the field of automated image recognition through the use of artificial neural networks, it will be possible to perform real-time observation at airports in the future.

The Institute of Atmospheric Physics at DLR Oberpfaffenhofen aims to reduce the risk of wake vortices and thus to reduce aircraft separation. During a recently completed measurement campaign lasting six months at Vienna International Airport, an extensive data set was generated and evaluated in large parts. The evaluation mainly relates to the location and the strength of the wake vortex. The evaluations are now to be used to set up an artificial neural network and to train with the existing data. The trained network will enable real-time monitoring of wake vortices with LIDAR systems at airports and ultimately make air traffic safer and more efficient.

Your tasks:

setting up an artificial neural network
training of this ANN with already gained data
evaluation and verification
Methoden: lidar, fluid dynamics, artificial neuronal networks
Anfangsdatum: 1. Februar 2020
Geschätzte Dauer: 6-12 Monate
Bezahlung: TvÖD 5