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Precise Single-Frequency Positioning Using Low-Cost Receiver with the Aid of Lane-Level Map Matching for Land Vehicle Navigation

Published online by Cambridge University Press:  23 July 2020

Fei Liu
Affiliation:
(Department of Civil Engineering, University of Calgary, Calgary, Alberta, Canada)
Yue Liu
Affiliation:
(College of Automation, Harbin Engineering University, Harbin, Heilongjiang, China)
Zhixi Nie
Affiliation:
(College of Oceanography and Space Informatics, China University of Petroleum, Qingdao, China)
Yang Gao
Affiliation:
(Department of Geomatics Engineering, University of Calgary, Calgary, Alberta, Canada)
Corresponding
E-mail address:

Abstract

Precise positioning with low-cost single-frequency global navigation satellite system (GNSS) receivers has great potential in a wide range of applications because of its low price and improved accuracy. However, challenges remain in achieving reliable and accurate solutions using low-cost receivers. For instance, the successful ambiguity fixing rate could be low for real-time kinematic (RTK) while large errors may occur in precise point positioning (PPP) in some scenarios (e.g., trees along the road). To solve the problems, this paper proposes a method with the aid of additional lane-level digital map information to improve the accuracy and reliability of RTK and PPP solutions. In the method, a digital camera will be applied for lane recognition and the positioning solution from a low-cost receiver will be projected to the digital map lane link. With the projected point position as a constraint, the RTK ambiguity fixing rate and PPP performance can be enhanced. A field kinematic test was conducted to verify the improvement of the RTK and PPP solutions with the aid of map matching. The results show that the RTK ambiguity fixing rate can be increased and the PPP positioning error can be reduced by map matching.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2020

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Precise Single-Frequency Positioning Using Low-Cost Receiver with the Aid of Lane-Level Map Matching for Land Vehicle Navigation
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