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Bounding Localization Errors With Student Distribution For Road Vehicles

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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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Dates and versions

hal-01942233 , version 1 (05-12-2018)

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Joelle Al Hage, Philippe Xu, Philippe Bonnifait. Bounding Localization Errors With Student Distribution For Road Vehicles. 5th International Technical Symposium on Navigation and Timing (ITSNT 2018), Oct 2018, Toulouse, France. ⟨10.31701/itsnt2018.11⟩. ⟨hal-01942233⟩
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