Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-29T06:45:02.375Z Has data issue: false hasContentIssue false
  • English
  • Français

A novel partial ambiguity method for multi-GNSS real-time kinematic positioning

Published online by Cambridge University Press:  15 July 2021

Haiyang Li ,
Guigen Nie ,
Jing Wang ,
Shuguang Wu  and
Yuefan He
Haiyang Li
Affiliation:
GNSS Research Center, Wuhan University, Wuhan, China
Guigen Nie*
Affiliation:
GNSS Research Center, Wuhan University, Wuhan, China
Jing Wang
Affiliation:
GNSS Research Center, Wuhan University, Wuhan, China
Shuguang Wu
Affiliation:
GNSS Research Center, Wuhan University, Wuhan, China
Yuefan He
Affiliation:
GNSS Research Center, Wuhan University, Wuhan, China
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Recent progress in using real-time kinematic (RTK) positioning has motivated the exploration of its application due to its high accuracy and efficiency. However, poorly-observed satellite data will cause unfixed ambiguities and markedly biased solutions. A novel partial ambiguity resolution method, named the irrespective of integer ambiguity resolution (IIAR) model, is proposed and applied to improve the reliability of ambiguity resolution. The proposed method contains initial ambiguity resolution and irrespective of integer ambiguity processes. The initial ambiguity resolution process applies an iterative partial ambiguity resolution method to obtain an approximate solution. The irrespective of integer ambiguity process transforms the approximate solution to a high-precision solution. Experiments show that the approximate solution is unreliable when the initial ambiguity resolution process has small redundancy, and the proposed method can obtain better results for those cases. The IIAR method showed about a 40% improvement of multi-GNSS ambiguity success rate and about a 25% improvement of standard deviation. Therefore, these results show that the proposed IIAR method can improve the results of multi-GNSS RTK positioning significantly.

Keywords

RTKpartial ambiguity resolutioninitial ambiguity resolutionirrespective of integer ambiguity resolution
Type
Research Article
Information
The Journal of Navigation , Volume 75 , Issue 3 , May 2022 , pp. 540 - 553
Check for updates
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Dai, L., Eslinger, D. and Sharpe, T. (2007). Innovative Algorithms to Improve Long-Range RTK Reliability and Availability. Proceedings of the 2007 National Technical Meeting of the Institute of Navigation, pp. 860–872.Google Scholar
Deng, C., Tang, W., Liu, J. and Shi, C. (2014). Reliable single-epoch ambiguity resolution for short baselines using combined GPS/BeiDou system. GPS Solutions, 18(3), 375–386.CrossRefGoogle Scholar
Edwards, S. J., Cross, P. A., Barnes, J. B. and Bataille, D. (1999). A methodology for benchmarking real-time kinematic GPS. Survey Review, 35(273), 163–174.CrossRefGoogle Scholar
Feng, Y. (2008). GNSS three carrier ambiguity resolution using ionosphere-reduced virtual signals. Journal of Geodesy, 82(12), 847–862.CrossRefGoogle Scholar
Ge, M., Gendt, G., Dick, G. and Zhang, F. (2005). Improving carrier-phase ambiguity resolution in global GPS network solutions. Journal of Geodesy, 79(1), 103–110.CrossRefGoogle Scholar
He, H., Li, J., Yang, Y., Xu, J., Guo, H. and Wang, A. (2014). Performance assessment of single- and dual-frequency BeiDou/GPS single-epoch kinematic positioning. GPS Solutions, 18(3), 393–403.CrossRefGoogle Scholar
Jonge, D. and Tiberius, C. (1998). The LAMBDA method for integer ambiguity estimation: Implementation aspects LGR-Series. No. 12. Technical report, Delft University of Technology, The Netherlands.Google Scholar
Li, J., Yang, Y., Xu, J., He, H. and Guo, H. (2015). GNSS multi-carrier fast partial ambiguity resolution strategy tested with real BDS/GPS dual- and triple-frequency observations. GPS Solutions, 19(1), 5–13.CrossRefGoogle Scholar
Liu, Z. (2014). GNSS Slope Monitoring and Deformation Analysis. Surveying and Mapping Press.Google Scholar
Odolinski, R., Teunissen, P. J. G. and Odijk, D. (2015). Combined BDS, Galileo, QZSS and GPS single-frequency RTK. GPS Solutions, 19(1), 151–163.CrossRefGoogle Scholar
Parkins, A. (2011). Increasing GNSS RTK availability with a new single-epoch batch partial ambiguity resolution algorithm. GPS Solutions, 15(4), 391–402.CrossRefGoogle Scholar
Paziewski, J. and Wielgosz, P. (2015). Accounting for Galileo-GPS inter-system biases in precise satellite positioning. Journal of Geodesy, 89, 81–93.CrossRefGoogle Scholar
Position Location and NaTeunissen, P. J. G. (1994). A New Method for Fast Carrier Phase Ambiguity Estimation. Position Location and Navigation Symposium, 562-573, IEEE.Google Scholar
Takasu, T. and Yasuda, A. (2010). Kalman-Filter-Based Integer Ambiguity Resolution Strategy for Long-Baseline RTK with Ionospheric and Troposphere Estimation. Proceedings of the ION GNSS 2010, Portland, OR, USA, pp. 161–171.Google Scholar
Teunissen, P. J. G. (1995). The least-square ambiguity decorrelation adjustment: A method for fast GPS ambiguity estimation. Journal of Geodesy, 70(1), 65–82.CrossRefGoogle Scholar
Teunissen, P. J. G. (1998). Success probability of integer GPS ambiguity rounding and bootstrapping. Journal of Geodesy, 72(10), 606–612.CrossRefGoogle Scholar
Teunissen, P. J. G. (1999). An optimality property of the integer least-squares estimator. Journal of Geodesy, 73(11), 587–593.CrossRefGoogle Scholar
Teunissen, P. J. G. (2001). GNSS Ambiguity Bootstrapping: Theory and Applications. In Proc. KIS2001, International Symposium on Kinematic Systems in Geodesy, Geomatics and Navigation, Banff, Canada, Vol. 2, pp. 246–254.Google Scholar
Teunissen, P. J. G., Joosten, P. and Tiberius, C. (1999). Geometry-free Ambiguity Success Rates in Case of Partial Fixing. Proceedings of the National Technical Meeting of the Institute of Navigation. San Diego, CA. pp. 201–207.Google Scholar
Torre, A. D. and Caporali, A. (2015). An analysis of intersystem biases for multi-GNSS positioning. GPS Solutions, 19(2), 297–307.CrossRefGoogle Scholar
Wang, J. and Feng, Y. (2013). Reliability of partial ambiguity fixing with multiple GNSS constellations. Journal of Geodesy, 87(1), 1–14.CrossRefGoogle Scholar
Xu, P., Shi, C. and Liu, J. (2012). Integer estimation methods for GPS ambiguity resolution: An applications-oriented review and improvement. Survey Review, 44(324), 59–71.CrossRefGoogle Scholar
Zhang, Y., Xu, S., Wang, Z. and Zhang, X. (2001). Processing of ambiguity in GPS / GLONASS integrated positioning. Journal of Wuhan University (Information Science Edition, 26 (001), 58–63.Google Scholar
Zhang, X., Liu, J. and Li, Z. (2003). An Ambiguity Free Model for Deformation Detection with GPS. Proceedings of the 16th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS/GNSS 2003), Portland, pp. 2617–2621.Google Scholar
Zhodzishsky, M., Vorobiev, M., Khvalkov, A. and Ashjaee, J. (1998). Real-Time Kinematic (RTK) Processing for Dual-Frequency GPS/GLONASS. Proceedings of the 11th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 1998), Nashville, TN, September, pp. 1325–1331.Google Scholar