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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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Submitted on : Wednesday, December 5, 2018 - 10:11:36 AM
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Joelle Al Hage, Philippe Xu, Philippe Bonnifait. Bounding Localization Errors With Student Distribution For Road Vehicles. International Technical Symposium on Navigation and Timing (ITSNT 2018), Oct 2018, Toulouse, France. ⟨10.31701/itsnt2018.11⟩. ⟨hal-01942233⟩



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