Bounding Localization Errors With Student Distribution For Road Vehicles

Abstract : GNSSintegrityisusuallylinkedtosafetycriticalapplications and, therefore, it includes the ability of a system to provide a warning to users when it should not be used. Recently, theintegrityconceptbecameanimportantissueforthetransportation sector especially with the growth of technology for autonomous vehicles that will be on the roads in the coming years. Inthiswork,weproposeamethodforboundinglocalization errors in automotive contexts. The approach begins with a multi-sensor data fusion with Fault Detection and Exclusion (FDE). The purpose is to isolate as much as possible detected faults before assessing the external integrity (Protection Level - PL) of the localization solution. For PL calculation, we propose to replace the classical Gaussian distribution assumption by a Student’s distribution which reflects morethedatadistributionparticularlyinurbanenvironments. The performances of the proposed approach and of the computed PL are studied on a experimental trajectory done at Compiègne, France.
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Communication dans un congrès
ITSNT 2018, International Technical Symposium on Navigation and Timing, Oct 2018, Toulouse, France
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https://hal-enac.archives-ouvertes.fr/hal-01942233
Contributeur : Laurence Porte <>
Soumis le : mercredi 5 décembre 2018 - 10:11:36
Dernière modification le : mercredi 9 janvier 2019 - 15:14:01

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Joelle Al Hage, Philippe Xu, Philippe Bonnifait. Bounding Localization Errors With Student Distribution For Road Vehicles. ITSNT 2018, International Technical Symposium on Navigation and Timing, Oct 2018, Toulouse, France. 〈hal-01942233〉

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