Skip to main content
Log in

Understanding long-term variations in GPS differential code biases

  • Original Article
  • Published:
GPS Solutions Aims and scope Submit manuscript

Abstract

Precise estimation of satellite differential code biases (DCBs) plays a crucial role in precise ionospheric modeling, positioning, and timing. Due to the rank deficiency, a constraint or a datum is required in order to separate the satellite DCBs from the receiver DCBs. A common practice is to impose a zero-mean constraint on all the visible satellites. However, datum selection is affected by satellite replacement and variation of the DCBs. As a result, the long-term variations of current DCB products vary significantly. Taking the DCBs of SVN 44 (PRN 28) as a reference, we analyzed the long-term variations of DCBs over a period of 20 years, between 2000 and 2019. Based on this reference, the results indicate that the change of the zero-mean datum is responsible for the variation of current DCB products. The datum change is attributed to the satellite replacement as well as the discontinuities and their variations. We found that discontinuities for the same satellite vehicle reach 1.8 ns, which is related to satellite changes announced in the Notice Advisory to Navstar Users message and to flex power. The magnitude of the DCBs depends on the satellite type. DCBs for Block IIR-A and IIR-M satellites are close to each other, while DCBs of Block IIR-B satellites are approximately 5 ns larger and DCBs for the Block IIF are 8 ns smaller. In addition, the satellite biases between GPS P1 and C1 are also briefly examined, and the results show that they are also affected by the satellite replacements and discontinuities. However, the satellite bias differences between P1 and C1 for different satellite types are minor.

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

Access this article

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
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  • Banville S, Zhang W, Ghoddousi-Fard R, Langley RB (2012) Ionospheric monitoring using “integer-levelled” observations. In: Proceedings of the ION GNSS 2012, Institute of Navigation. Nashville, Tennessee, USA, September 17–21, pp 2692–2701

  • Coco DS, Coker C, Dahlke SR, Clynch JR (1991) Variability of GPS satellite differential group delay biases. IEEE Trans Aerosp Electron Syst 27(6):931–938. https://doi.org/10.1109/7.104264

    Article  Google Scholar 

  • Coster A, Williams J, Weatherwax A, Rideout W, Herne D (2013) Accuracy of GPS total electron content: GPS receiver bias temperature dependence. Radio Sci 48(2):190–196. https://doi.org/10.1002/rds.20011

    Article  Google Scholar 

  • Dach R, Hugentobler U, Fridez P, Meindl M (2015) Bernese GPS software version 5.2. Astronomical Institute, University of Bern

  • Gao Y, Lahaye F, Héroux P, Liao X, Beck N, Olynik M (2001) Modeling and estimation of C1–P1 bias in GPS receivers. J Geod 74(9):621–626

    Article  Google Scholar 

  • Hauschild A, Montenbruck O (2016) A study on the dependency of GNSS pseudorange biases on correlator spacing. GPS Solut 20(2):159–171

    Article  Google Scholar 

  • Hegarty CJ, Powers ED, Fonville B (2005) Accounting for timing biases between GPS, modernized GPS, and Galileo signals. In: Proceedings of the ION GNSS 2005, Institute of Navigation. Long Beach, CA, US, September 16–19, pp 2401–2407

  • Hernández-Pajares M, Juan JM, Sanz J, Orus R, Garcia-Rigo A, Feltens J, Komjathy A, Schaer SC, Krankowski A (2009) The IGS VTEC maps: a reliable source of ionospheric information since 1998. J Geod 83(3–4):263–275

    Article  Google Scholar 

  • Levine J (2008) A review of time and frequency transfer methods. Metrologia 45(6):S162

    Article  Google Scholar 

  • Li H, Li B, Lou L, Yang L, Wang J (2016) Impact of GPS differential code bias in dual- and triple-frequency positioning and satellite clock estimation. GPS Solut. https://doi.org/10.1007/s10291-016-0578-1

    Article  Google Scholar 

  • Li M, Yuan Y, Wang N, Li Z, Li Y, Huo X (2017) Estimation and analysis of Galileo differential code biases. J Geodesy 91(3):279–293

    Article  Google Scholar 

  • Li Z, Yuan Y, Li H, Ou J, Huo X (2012) Two-step method for the determination of the differential code biases of COMPASS satellites. J Geod 86(11):1059–1076

    Article  Google Scholar 

  • Mannucci AJ, Wilson BD, Yuan DN, Ho CH, Lindqwister UJ, Runge TF (1998) A global mapping technique for GPS-derived ionospheric total electron content measurements. Radio Sci 33(3):565–582

    Article  Google Scholar 

  • Montenbruck O, Hauschild A, Steigenberger P (2014) Differential code bias estimation using multi-GNSS observations and global ionosphere maps. Navigation 61(3):191–201

    Article  Google Scholar 

  • Ray J, Senior K (2005) Geodetic techniques for time and frequency comparisons using GPS phase and code measurements. Metrologia 42(4):215–232

    Article  Google Scholar 

  • Rovira-Garcia A, Juan JM, Sanz J, Gonzalez-Casado G (2015) A worldwide ionospheric model for fast precise point positioning. IEEE Trans Geosci Remote Sens 53(8):4596–4604

    Article  Google Scholar 

  • 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(5):1899–1910

    Article  Google Scholar 

  • Steigenberger P, Thölert S, Montenbruck O (2019) Flex power on GPS block IIR-M and IIF. GPS Solut 23(1):8

    Article  Google Scholar 

  • Tu R, Zhang P, Zhang R, Liu J, Lu X (2019) Modeling and performance analysis of precise time transfer based on BDS triple-frequency un-combined observations. J Geod 93(6):837–847

    Article  Google Scholar 

  • Villiger A, Schaer S, Dach R, Prange L, Sušnik A, Jäggi A (2019) Determination of GNSS pseudo-absolute code biases and their long-term combination. J Geod 93(9):1487–1500. https://doi.org/10.1007/s00190-019-01262-w

    Article  Google Scholar 

  • Wang N, Yuan Y, Li Z, Montenbruck O, Tan B (2016) Determination of differential code biases with multi-GNSS observations. J Geod 90(3):209–228

    Article  Google Scholar 

  • Wanninger L, Sumaya H, Beer S (2017) Group delay variations of GPS transmitting and receiving antennas. J Geod 91(9):1099–1116

    Article  Google Scholar 

  • Xiang Y (2018) Carrier phase-based ionospheric modeling and augmentation in uncombined precise point positioning. Dissertation, University of Calgary, Calgary, Canada

  • Xiang Y, Gao Y (2017) Improving DCB estimation using uncombined PPP. Navigation 64(4):463–473

    Article  Google Scholar 

  • Yuan Y, Ou J (2004) Generalized trigonometric series function model for determining ionospheric delay. Prog Nat Sci 14(11):1010–1014

    Article  Google Scholar 

  • Zhang B, Teunissen PJG, Yuan Y (2017) On the short-term temporal variations of GNSS receiver differential phase biases. J Geod 91(5):563–572

    Article  Google Scholar 

  • Zhang BC, Ou JK, Bin YY, Li ZS (2012) Extraction of line-of-sight ionospheric observables from GPS data using precise point positioning. Sci China Earth Sci 55(11):1919–1928

    Article  Google Scholar 

  • Zhang D, Shi H, Jin Y, Zhang W, Hao Y, Xiao Z (2014) The variation of the estimated GPS instrumental bias and its possible connection with ionospheric variability. Sci China Technol Sci 57(1):67–79

    Article  Google Scholar 

  • Zhao L, Ye S, Song J (2017) Handling the satellite inter-frequency biases in triple-frequency observations. Adv Space Res 59(8):2048–2057. https://doi.org/10.1016/j.asr.2017.02.002

    Article  Google Scholar 

  • Zhong J, Lei J, Dou X, Yue X (2016a) Is the long-term variation of the estimated GPS differential code biases associated with ionospheric variability? GPS Solut 20(3):313–319

    Article  Google Scholar 

  • Zhong J, Lei J, Yue X, Dou X (2016b) Determination of differential code bias of GNSS receiver onboard low earth orbit satellite. IEEE Trans Geosci Remote Sens 54(8):4896–4905

    Article  Google Scholar 

Download references

Acknowledgements

DCB products downloaded from CODE and NANU information are gratefully acknowledged. We also thank anonymous reviewers for their useful comments and suggestions on the research that led to this manuscript. Special thanks to IEEE life fellow Trieu-Kien Truong and Daniele Sartori’s proofreading. The study is supported by the science and technology project of State Grid Corporation of China (No. SGSHJX00KXJS1901531).

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Yan Xiang or Zhexin Xu.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xiang, Y., Xu, Z., Gao, Y. et al. Understanding long-term variations in GPS differential code biases. GPS Solut 24, 118 (2020). https://doi.org/10.1007/s10291-020-01034-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10291-020-01034-6

Keywords

Navigation