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Multi-GNSS fractional cycle bias products generation for GNSS ambiguity-fixed PPP at Wuhan University

  • Jiahuan Hu
  • Xiaohong Zhang
  • Pan LiEmail author
  • Fujian Ma
  • Lin Pan
Original Article
  • 170 Downloads

Abstract

The School of Geodesy and Geomatics (SGG) at Wuhan University has been generating GPS fractional cycle bias (FCB) products for users to realize ambiguity-fixed precise point positioning (PPP) since 2015. Along with the development of multiple Global Navigation Satellite Systems (GNSS), there is an urgent need to provide multi-GNSS FCB products for the PPP ambiguity resolution (AR) with multi-constellation observations. This study focuses on the multi-GNSS FCB estimation, in which the FCB products of GPS, Galileo, BDS and QZSS are generated. We describe here the detailed estimation method and the significant improvements to the new service. The FCB quality, as well as the PPP AR performance, is evaluated. The mean standard deviations of wide-lane FCBs relative to CODE are 0.019, 0.005, 0.015 and 0.008 cycles, while those of narrow-lane are 0.021, 0.021, 0.057 and 0.010 cycles for GPS, Galileo, BDS and QZSS, respectively. The comparison with CNES GPS and Galileo FCBs indicates their good consistency with the corresponding FCBs. Compared with GPS-only PPP AR, the convergence time and time to first fix of the four-system PPP AR can be reduced by 27.3 and 29.4% in the static mode, respectively, while the corresponding improvements are 42.6 and 51.9% in the kinematic mode, respectively. These results demonstrate that our SGG FCB service can provide high-precision and reliable four-system FCB corrections for worldwide users to conduct ambiguity-fixed PPP processing.

Keywords

Multi-GNSS Fractional cycle bias Precise point positioning Ambiguity resolution 

Notes

Acknowledgements

This study was supported by China National Funds for Distinguished Young Scientists (No. 41825009). The authors are grateful to the many individuals and organizations worldwide who contribute to the International GNSS Service.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Jiahuan Hu
    • 1
  • Xiaohong Zhang
    • 1
    • 2
  • Pan Li
    • 3
    Email author
  • Fujian Ma
    • 1
  • Lin Pan
    • 4
  1. 1.School of Geodesy and GeomaticsWuhan UniversityWuhanChina
  2. 2.Collaborative Innovation Center for Geospatial TechnologyWuhanChina
  3. 3.German Research Centre for Geosciences (GFZ)PotsdamGermany
  4. 4.School of Geosciences and Info-PhysicsCentral South UniversityChangshaChina

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