Seamless Accurate Positioning in Deep Urban Area Based on Mode Switching Between DGNSS and Multipath Mitigation Positioning

Multipath and non-line-of-sight (NLOS) signals are the major causes of poor accuracy of a global navigation satellite system (GNSS) in urban areas. Despite the wide usage of the GNSS in populated urban areas, it is difficult to suggest a generalized method because multipath errors are user-specific...

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Bibliographic Details
Published in:IEEE transactions on intelligent transportation systems 2023-06, Vol.24 (6), p.1-15
Main Authors: Lee, Yongjun, Hwang, Yoola, Ahn, Jae Young, Seo, Jiwon, Park, Byungwoon
Format: Article
Language:English
Subjects:
Algorithms
Automobile industry
Buildings
Deep urban area positioning
differential GNSS
Error reduction
Global navigation satellite system
Intelligent transportation systems
Kinematics
multipath
non-line-of-sight error
Real time
Receivers
Satellites
Sensors
Switches
Switching theory
Urban areas
Urban environments
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Summary:Multipath and non-line-of-sight (NLOS) signals are the major causes of poor accuracy of a global navigation satellite system (GNSS) in urban areas. Despite the wide usage of the GNSS in populated urban areas, it is difficult to suggest a generalized method because multipath errors are user-specific and cannot be eliminated by the differential GNSS (DGNSS) or a real-time kinematic technique (RTK). This paper introduces a real-time multipath estimation and mitigation technique which considers compensation for the time offset between constellations. It also presents a mode-switching algorithm between the DGNSS and multipath mitigating mode and shows that this technique can be effectively utilized for automobiles in a deep urban environment without any help from sensors other than GNSS. The availability is improved from 64% to 100% and the error RMS is reduced from 11.1 m to 1.2 m on Teheran-ro, Seoul, Korea. Because this method does not require prior information or additional sensor implementation for high-positioning performance in deep urban areas, it is expected to gain wide usage in not only the automotive industry but also future intelligent transportation systems.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2023.3256040