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Accounting for Inter-System Bias in DGNSS Positioning with GPS/GLONASS/BDS/Galileo

Published online by Cambridge University Press:  01 February 2017

Hui Liu
Affiliation:
(GNSS Research Center, Wuhan University, Wuhan, China)
Bao Shu*
Affiliation:
(GNSS Research Center, Wuhan University, Wuhan, China)
Longwei Xu
Affiliation:
(GNSS Research Center, Wuhan University, Wuhan, China)
Chuang Qian
Affiliation:
(GNSS Research Center, Wuhan University, Wuhan, China)
Rufei Zhang
Affiliation:
(GNSS Research Center, Wuhan University, Wuhan, China)
Ming Zhang
Affiliation:
(GNSS Research Center, Wuhan University, Wuhan, China)
*

Abstract

Code Differential Global Positioning System (DGPS) is widely used in satellite navigation and positioning because of its simple algorithm and preferable precision. Multi-Global Navigation Satellite System (GNSS) is expected to enhance the accuracy, reliability and availability of Differential GNSS (DGNSS) positioning. Traditional DGNSS models should set separate clock parameters due to the clock differences between the different systems. Awareness of the Inter-System Bias (ISB) could help to maximise the redundancy of the positioning model, thus improving the performance of multi-GNSS positioning. This paper aims to examine the inter-system bias of GPS/GLONASS/BeiDou (BDS)/Galileo and their benefits in DGNSS positioning. Results show that Differential ISB (DISB) characteristics vary with different receiver types and systems. The size of DISB could reach metre-level and the precision of estimated DISBs can reach approximately several centimetres within tens of epochs. Therefore, a new real-time DGNSS model that accounts for ISB is proposed. After differential ISBs are initialised, positioning with four satellites from arbitrarily the same or different systems can be realised. Moreover, compared with the traditional DGNSS model, the precision of the positioning results with the new model are obviously improved, especially in harsh environments.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2017 

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