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SAR data based Landmark Navigation for highly precise Vehicle Localization

Richter, David and Abmayr, Thomas and Runge, Hartmut (2016) SAR data based Landmark Navigation for highly precise Vehicle Localization. MoLaS 2016, 23. - 24.11.2016, Freiburg, Deutschland.

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Abstract

This approach deals with a probabilistic state estimation method with the aid of landmarks in the context of autonomous driving and driver assistance systems. It is mandatory to get a precise ego-position in order to operate vehicles throughout complex urban environments where global positioning methods like GPS provide only low position accuracies and low reliability. On-board sensors like LiDAR are able to detect a wide range of objects in the surrounding of a vehicle. Static urban objects like streetlamps or traffic light posts with absolute coordinates could be a solution to improve stability on the localization of a vehicle. Modern remote sensing approaches like geodetic radar are able to extract certain features like pole-shaped objects in an extensive and fast way. This work demonstrates the possibility of locating oneself within a landmark map based on a low-cost LiDAR sensor. Monte-Carlo localization enhances GPS positioning accuracy and was successfully applied on a test site.

Item URL in elib:https://elib.dlr.de/108356/
Document Type:Conference or Workshop Item (Poster)
Title:SAR data based Landmark Navigation for highly precise Vehicle Localization
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Richter, DavidDavid.Richter (at) dlr.deUNSPECIFIED
Abmayr, Thomasthomas.abmayr (at) hm.eduUNSPECIFIED
Runge, HartmutHartmut.Runge (at) dlr.deUNSPECIFIED
Date:23 November 2016
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Landmark, particle filter, Partikelfilter, SAR Geodesy, vehicle localization
Event Title:MoLaS 2016
Event Location:Freiburg, Deutschland
Event Type:Workshop
Event Dates:23. - 24.11.2016
Organizer:Fraunhofer IPM
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > SAR Signal Processing
Deposited By: Richter, David
Deposited On:25 Nov 2016 11:29
Last Modified:31 Jul 2019 20:05

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