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, 23:63 | Cite as

Precise point positioning ambiguity resolution by integrating BDS-3e into BDS-2 and GPS

  • Lizhong QuEmail author
  • Mingyi Du
  • Jian Wang
  • Yang Gao
  • Qile Zhao
  • Qiang Zhang
  • Xiang Guo
Original Article
  • 144 Downloads

Abstract

With the development of BDS-3, more BDS satellites are in orbits which can contribute to the reduction in the initial time of ambiguity fixing as well as the increase in the ambiguity fixing rate. We focus on the improvement in the BDS-based PPP AR as well as the GPS- and BDS-integrated PPP AR, using newly available BDS-3e satellites. To achieve this goal, the wide-lane (WL) and narrow-lane (NL) fractional cycle biases (FCBs) of B1I and B3I observations of BDS-2 IGSO and MEO satellites as well as of observations of BDS-3e satellites are generated using a network of globally distributed reference stations, while the BDS-2 GEO satellites are excluded from the FCBs estimation for their poor orbit accuracy due to the poor geometry. Both static and kinematic PPP AR solutions have been compared and analyzed in five combination strategies, including BDS-2 AR, BDS-2/3e AR, GPS AR, GPS/BDS-2 AR and GPS/BDS-2/3e AR. The experimental results illustrate that the inclusion of BDS-3e satellites is able to significantly improve the performance of the BDS-based PPP AR but only marginally improves the performance of the GPS- and BDS-integrated PPP AR. An average TTFF of 57.2 min (static) and 60.3 min (kinematic) and a fixing rate of 88.7% (static) and 87.3% (kinematic) have been achieved in the static and kinematic PPP AR for BDS-2/3e. The average time of TTFF is shortened to 15.3 min (static) and 16.4 min (kinematic) with a fixing rate of 96.9% (static) and 96.2% (kinematic) for GPS/BDS-2. The PPP AR of GPS/BDS-2/3e is found to perform the best among the five combination strategies of solutions, and an average TTFF of 13.1 min (static) and 14.3 min (kinematic) and a fixing rate of 97.0% (static) and 96.7% (kinematic) have been obtained.

Keywords

BDS-2/3e B1I and B3I observations Precise point positioning (PPP) Fractional cycle biases (FCBs) Ambiguity resolution (AR) 

Notes

Acknowledgements

We are grateful to the anonymous reviewers and the editor for their constructive suggestions. This work was partially supported by the National Key Research and Development Program of China (No. 2018YFC0706003), National Natural Science Foundation of China (No. 41874029), Beijing Advanced Innovation Center for Future Urban Design Major Project (No. UDC2018030611), General Research Project of Beijing Education Commission (KM201910016007) and Fundamental Research Funds for Beijing Universities (No. X18007).

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Copyright information

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

Authors and Affiliations

  1. 1.School of Geomatics and Urban Spatial InformationBeijing University of Civil, Engineering and ArchitectureBeijingPeople’s Republic of China
  2. 2.Key Laboratory of Modern Urban Surveying and MappingNational Administration of Surveying, Mapping and GeoinformationBeijingPeople’s Republic of China
  3. 3.Department of Geomatics EngineeringUniversity of CalgaryCalgaryCanada
  4. 4.GNSS Research CenterWuhan UniversityWuhanPeople’s Republic of China

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