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A System for Image-Based Non-Line-Of-Sight Detection Using Convolutional Neural Networks

Böker, Clarissa and Niemeijer, Joshua and Wojke, Nicolai and Meurie, Cyril and Cocheril, Yann (2019) A System for Image-Based Non-Line-Of-Sight Detection Using Convolutional Neural Networks. In: 2019 IEEE Intelligent Transportation Systems Conference (ITSC), pp. 535-540. IEEE. ITSC 2019, 27.-30. Okt. 2019, Auckland, New Zealand. DOI: 10.1109/ITSC.2019.8917272 ISBN 978-1-5386-7024-8

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Official URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8917272&isnumber=8916833


The ERSAT GGC project introduces the concept of virtual balises for train localization, which avoids investment and maintenance costs of physical balises. Since this concept relies on the matching of train positions to balise positions stored in a database, it is dependent on placing virtual balises in track areas with unimpeded GNSS reception. One factor majorly contributing to the distortion of GNSS signals is the non-line-of-sight (NLOS) scenario where the direct path between a satellite and the receiver on the train is blocked. As these NLOS situations result in deflections or the total absence of GNSS signals, this paper proposes a system to identify obstacles occluding the visibility of satellites above the tracks traversed by a train. This is achieved by video recording the sky from the roof of the train and segmenting the images into sky and non-sky regions. The line-of-sight status of individual satellites is found through projecting the known satellite locations into the segmented images. Consequently, the information whether a satellite is located in a sky or non-sky segment of the image allows for a determination of the GNSS performance at any observed track area.

Item URL in elib:https://elib.dlr.de/130942/
Document Type:Conference or Workshop Item (Speech)
Title:A System for Image-Based Non-Line-Of-Sight Detection Using Convolutional Neural Networks
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Böker, Clarissaclarissa.boeker (at) dlr.deUNSPECIFIED
Niemeijer, JoshuaJoshua.Niemeijer (at) dlr.deUNSPECIFIED
Wojke, NicolaiNicolai.Wojke (at) dlr.deUNSPECIFIED
Meurie, CyrilCyril.Meurie (at) ifsttar.frUNSPECIFIED
Cocheril, YannYann.Cocheril (at) ifsttar.frUNSPECIFIED
Date:28 November 2019
Journal or Publication Title:2019 IEEE Intelligent Transportation Systems Conference (ITSC)
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
DOI :10.1109/ITSC.2019.8917272
Page Range:pp. 535-540
Keywords:Non-Line-Of-Sight Detection, Convolutional Neural Networks
Event Title:ITSC 2019
Event Location:Auckland, New Zealand
Event Type:international Conference
Event Dates:27.-30. Okt. 2019
Organizer:IEEE Intelligent Transportation Systems Society
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Rail Transport
DLR - Research area:Transport
DLR - Program:V SC Schienenverkehr
DLR - Research theme (Project):V - Digitalisierung und Automatisierung des Bahnsystems
Location: Braunschweig
Institutes and Institutions:Institute of Transportation Systems
Deposited By: Böker, Clarissa
Deposited On:27 Nov 2019 09:33
Last Modified:10 Dec 2019 08:52

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