Skip to main content
SpringerLink
Log in

Characterization of multi-GNSS between-receiver differential code biases using zero and short baselines

  • Article
  • Earth Sciences
  • Published:
Science Bulletin

Abstract

Care should be taken to minimize adverse impact of receiver differential code biases (DCBs) on global navigation satellite system (GNSS)-derived ionospheric parameters. It is therefore of importance to ascertain the intrinsic characteristics of receiver DCBs, preferably in the context of new-generation GNSS. In this contribution, we present a method that enables time-wise retrieval of between-receiver DCBs (BR-DCBs) from dual-frequency, code-only measurements collected by a pair of co-located receivers. This method is applicable to the US GPS as well as to a new set of GNSS constellations including the Chinese BeiDou, the European Galileo and the Japanese QZSS. With the use of this method, we determine the multi-GNSS BR-DCB time-wise estimates covering a time period of up to 2 years (January 2013–March 2015) with a 30-s time resolution for five receiver-pairs (four zero and one short baselines). For the BR-DCB time-wise estimates pertaining to an arbitrary receiver-pair and constellation, we demonstrate their promising intraday stability by means of statistical hypothesis testing. We also find that the BeiDou BR-DCB daily weighted average (DWA) estimates show a dependence on satellite type, in particular for receiver-pairs of mixed types. Finally, we demonstrate that long-term variability in BR-DCB DWA estimates can be closely associated with hardware temperature variations inside the receivers.

摘要

利用全球导航卫星系统(global navigation satellite system, GNSS)研究电离层需要克服接收机差分码偏差(differential code bias, DCB)的不利影响。在新一代GNSS应用环境下, 准确地了解接收机DCB的相关特性尤为重要。本文报告了一种相对接收机DCB(between-receiver DCB, BR-DCB)的单历元估计方法, 其适用于美国GPS(global positioning system), 中国“北斗”、欧盟“伽利略”和日本“准天顶卫星系统”(quasi-zenith satellite system, QZSS)。通过处理5对接收机(含4组零基线和1组短基线)的多GNSS观测数据(采集于2013年1月至2015年3月, 30 s采样间隔), 本文获取并分析了相应的BR-DCB单历元估值。主要结论包括: BR-DCB单历元估值在一天内不存在显著变化; 由不同类 “北斗”卫星观测值所计算的BR-DCB估值可能会存在差异; BR-DCB估值的长期变化与接收机硬件温度高度相关。

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Li Z, Yuan Y, Wang N et al (2015) SHPTS: towards a new method for generating precise global ionospheric TEC map based on spherical harmonic and generalized trigonometric series functions. J Geodesy 89:331–345

    Article  Google Scholar 

  2. Liu L, Wan W, Chen Y et al (2011) Solar activity effects of the ionosphere: a brief review. Chin Sci Bull 56:1202–1211

    Article  Google Scholar 

  3. Mannucci A, Wilson B, Yuan D et al (1998) Global mapping technique for GPS-derived ionospheric total electron content measurements. Radio Sci 33:565–582

    Article  Google Scholar 

  4. Komjathy A, Wilson B, Pi X et al (2010) JPL/USC GAIM: on the impact of using COSMIC and ground-based GPS measurements to estimate ionospheric parameters. J Geophys Res 115:A02307

    Google Scholar 

  5. Hernández-Pajares M, Juan J, Sanz J et al (2009) The IGS VTEC maps: a reliable source of ionospheric information since 1998. J Geodesy 83:263–275

    Article  Google Scholar 

  6. Gu S, Shi C, Lou Y et al (2015) Ionospheric effects in uncalibrated phase delay estimation and ambiguity-fixed PPP based on raw observable model. J Geodesy 89:447–457

    Article  Google Scholar 

  7. Chen G, Zhao Q (2014) Near-field surface displacement and permanent deformation induced by the Alaska Mw 7.5 earthquake determined by high-rate real-time ambiguity-fixed PPP solutions. Chin Sci Bull 59:4781–4789

    Article  Google Scholar 

  8. Hernández-Pajares M, Juan JM, Sanz J et al (2011) The ionosphere: effects, GPS modeling and the benefits for space geodetic techniques. J Geodesy 85:887–907

    Article  Google Scholar 

  9. Liu Z, Skone S, Gao Y et al (2005) Ionospheric modeling using GPS data. GPS Solut 9:63–66

    Article  Google Scholar 

  10. Yuan Y, Tscherning CC, Knudsen P et al (2008) The ionospheric eclipse factor method (IEFM) and its application to determining the ionospheric delay for GPS. J Geodesy 82:1–8

    Article  Google Scholar 

  11. Yuan Y, Ou J (2002) Differential areas for differential stations (DADS): a new method of establishing grid ionospheric model. Chin Sci Bull 47:1033–1036

    Article  Google Scholar 

  12. Spits J, Warnant R (2008) Total electron content monitoring using triple frequency GNSS data: a three-step approach. J Atmos Sol-Terr Phys 70:1885–1893

    Article  Google Scholar 

  13. Le AQ (2006) Impact of Galileo on global ionosphere map estimation. J Navig 59:281–292

    Article  Google Scholar 

  14. Tang W, Jin L, Xu K (2014) Performance analysis of ionosphere monitoring with BeiDou CORS observational data. J Navig 67:511–522

    Article  Google Scholar 

  15. Yang Y, Li J, Xu J et al (2011) Contribution of the compass satellite navigation system to global PNT users. Chin Sci Bull 56:2813–2819

    Article  Google Scholar 

  16. Lou Y, Liu Y, Shi C et al (2014) Precise orbit determination of BeiDou constellation based on BETS and MGEX network. Sci Rep. doi:10.1038/srep04692

    Google Scholar 

  17. Steigenberger P, Hugentobler U, Montenbruck O et al (2011) Precise orbit determination of GIOVE-B based on the CONGO network. J Geodesy 85:357–365

    Article  Google Scholar 

  18. Hauschild A, Steigenberger P, Rodriguez-Solano C (2012) Signal, orbit and attitude analysis of Japan’s first QZSS satellite Michibiki. GPS Solut 16:127–133

    Article  Google Scholar 

  19. Kawano I, Mokuno M, Kogure S et al (2004) Japanese experimental GPS augmentation using quasi-zenith satellite system (QZSS). In: Proceedings of the Institute of Navigation (ION) GNSS 2004, Long Beach

  20. Sardon E, Rius A, Zarraoa N (1994) Estimation of the transmitter and receiver differential biases and the ionospheric total electron content from Global Positioning System observations. Radio Sci 29:577–586

    Article  Google Scholar 

  21. Li Z, Yuan Y, Fan L et al (2014) Determination of the differential code bias for current BDS satellites. IEEE Trans Geosci Remote Sens 52:3968–3979

    Article  Google Scholar 

  22. Sardón E, Zarraoa N (1997) Estimation of total electron content using GPS data: how stable are the differential satellite and receiver instrumental biases? Radio Sci 32:1899–1910

    Article  Google Scholar 

  23. Li Z, Yuan Y, Li H et al (2012) Two-step method for the determination of the differential code biases of COMPASS satellites. J Geodesy 86:1059–1076

    Article  Google Scholar 

  24. Montenbruck O, Hauschild A, Steigenberger P (2014) Differential code bias estimation using multi-GNSS observations and global ionosphere maps. Navig J Inst Navig 61:191–201

    Article  Google Scholar 

  25. Ciraolo L, Azpilicueta F, Brunini C et al (2007) Calibration errors on experimental slant total electron content (TEC) determined with GPS. J Geodesy 81:111–120

    Article  Google Scholar 

  26. Brunini C, Azpilicueta FJ (2009) Accuracy assessment of the GPS-based slant total electron content. J Geodesy 83:773–785

    Article  Google Scholar 

  27. Coster A, Williams J, Weatherwax A et al (2013) Accuracy of GPS total electron content: GPS receiver bias temperature dependence. Radio Sci 48:190–196

    Article  Google Scholar 

  28. Zhang D, Shi H, Jin Y et al (2014) The variation of the estimated GPS instrumental bias and its possible connection with ionospheric variability. Sci China Technol Sci 57:67–79

    Article  Google Scholar 

  29. Zhang D, Zhang W, Li Q et al (2010) Accuracy analysis of the GPS instrumental bias estimated from observations in middle and low latitudes. Ann Geophys 28:1571–1580

    Article  Google Scholar 

  30. Zhang W, Zhang D, Xiao Z (2009) The influence of geomagnetic storms on the estimation of GPS instrumental biases. Ann Geophys 27:1613–1623

    Article  Google Scholar 

  31. Zhong J, Lei J, Dou X et al (2015) Is the long-term variation of the estimated GPS differential code biases associated with ionospheric variability? GPS Solut. doi:10.1007/s10291-015-0437-5

    Google Scholar 

  32. Zhang B, Ou J, Yuan Y et al (2012) Extraction of line-of-sight ionospheric observables from GPS data using precise point positioning. Sci China Earth Sci 55:1919–1928

    Article  Google Scholar 

  33. Stephens P, Komjathy A, Wilson B et al (2011) New leveling and bias estimation algorithms for processing COSMIC/FORMOSAT-3 data for slant total electron content measurements. Radio Sci. doi:10.1029/2010RS004588

    Google Scholar 

  34. Nadarajah N, Teunissen P, Raziq N (2013) BeiDou inter-satellite-type bias evaluation and calibration for mixed receiver attitude determination. Sensors 13:9435–9463

    Article  Google Scholar 

  35. Freedman DA (2009) Statistical models: theory and practice. Cambridge University Press, London

    Book  Google Scholar 

Download references

Acknowledgments

We would like to express our gratitude to Dr. Oliver Montenbruck and Dr. Jean-Marie Sleewaegen for their thoughtful suggestions and extensive discussions. Special thanks go to Dr. Nandakumaran Nadarajah and Mr. Matt Carver for collecting the multi-GNSS experimental data and to Bureau of Meteorology (Australia) for providing the online climate data. This work has been executed in the framework of the Positioning Program Project 1.19 “Multi-GNSS PPP-RTK Network Processing” of the Cooperative Research Centre for Spatial Information (CRC-SI). This work was also partially funded by the Chinese Academy of Sciences (CAS) and the Royal Netherlands Academy of Arts and Sciences (KNAW) joint research project “Compass, Galileo and GPS for improved ionosphere modelling.” The second author is the recipient of an Australian Research Council (ARC) Federation Fellowship (NO. FF0883188). All this support is gratefully acknowledged.

Conflict of interest

The authors declare that they have no conflict of interest.

Author information

Authors and Affiliations

  1. Global Navigation Satellite System (GNSS) Research Centre, Curtin University, Perth, Australia

    Baocheng Zhang & Peter J. G. Teunissen

  2. Geoscience and Remote Sensing, Delft University of Technology, Delft, The Netherlands

    Peter J. G. Teunissen

Authors
  1. Baocheng Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Peter J. G. Teunissen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Baocheng Zhang.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (PDF 541 kb)

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, B., Teunissen, P.J.G. Characterization of multi-GNSS between-receiver differential code biases using zero and short baselines. Sci. Bull. 60, 1840–1849 (2015). https://doi.org/10.1007/s11434-015-0911-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11434-015-0911-z

Keywords

Search

Navigation