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Evaluating machine learning & antenna placement for enhanced GNSS accuracy for CAVs
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Adegoke, Elijah, Zidan, Jasmine, Kampert, Erik, Jennings, P. A. (Paul A.), Ford, Colin, Birrell, Stewart A. and Higgins, Matthew D. (2019) Evaluating machine learning & antenna placement for enhanced GNSS accuracy for CAVs. In: 2019 IEEE Intelligent Vehicles Symposium, Paris, France, 9-12 Jun 2019. Published in: 2019 IEEE Intelligent Vehicles Symposium (IV) doi:10.1109/IVS.2019.8813775
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WRAP-evaluating-machine-learning-antenna-placement-enhanced-GNSS-accuracy-CAVs-Jennings-2019.pdf - Accepted Version - Requires a PDF viewer. Download (1325Kb) | Preview |
Official URL: https://doi.org/10.1109/IVS.2019.8813775
Abstract
Localization accuracy obtainable from global navigation
satellites systems in built up areas like urban canyons
and multi-storey car parks is severely impaired due to multipath and non-line-of-sight signal propagation. In this paper, a simple classifier was used in discriminating between multipath and line-of-sight GNSS signals. By using the carrier to noise ratio which characterizes the received signal strength of the GNSS signals, and the rate of change of the epochs of the satellite vehicles in view, a prediction accuracy of 98% was attained from the classifier. Also investigated in this paper is the effect of antenna placement on localization accuracy. Our measurement
campaign using a Nissan Leaf hatch back model showed that the centre longitudinal line of the roof generated the least localization errors for an urbanized route.
Item Type: | Conference Item (Paper) | |||||||||||||||
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Subjects: | T Technology > TL Motor vehicles. Aeronautics. Astronautics | |||||||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | |||||||||||||||
Library of Congress Subject Headings (LCSH): | Artificial satellites in navigation, Global Positioning System, Location-based services, Autonomous vehicles, Machine learning | |||||||||||||||
Journal or Publication Title: | 2019 IEEE Intelligent Vehicles Symposium (IV) | |||||||||||||||
Publisher: | IEEE | |||||||||||||||
Official Date: | 29 August 2019 | |||||||||||||||
Dates: |
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DOI: | 10.1109/IVS.2019.8813775 | |||||||||||||||
Status: | Peer Reviewed | |||||||||||||||
Publication Status: | Published | |||||||||||||||
Reuse Statement (publisher, data, author rights): | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |||||||||||||||
Access rights to Published version: | Restricted or Subscription Access | |||||||||||||||
Date of first compliant deposit: | 26 July 2019 | |||||||||||||||
Date of first compliant Open Access: | 29 July 2019 | |||||||||||||||
Grant number: | 95143-564624 | |||||||||||||||
RIOXX Funder/Project Grant: |
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Conference Paper Type: | Paper | |||||||||||||||
Title of Event: | 2019 IEEE Intelligent Vehicles Symposium | |||||||||||||||
Type of Event: | Conference | |||||||||||||||
Location of Event: | Paris, France | |||||||||||||||
Date(s) of Event: | 9-12 Jun 2019 | |||||||||||||||
Related URLs: |
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