Skip to main content
Log in

Estimation and analysis of Galileo differential code biases

  • Original Article
  • Published:
Journal of Geodesy Aims and scope Submit manuscript


When sensing the Earth’s ionosphere using dual-frequency pseudorange observations of global navigation satellite systems (GNSS), the satellite and receiver differential code biases (DCBs) account for one of the main sources of error. For the Galileo system, limited knowledge is available about the determination and characteristic analysis of the satellite and receiver DCBs. To better understand the characteristics of satellite and receiver DCBs of Galileo, the IGGDCB (IGG, Institute of Geodesy and Geophysics, Wuhan, China) method is extended to estimate the satellite and receiver DCBs of Galileo, with the combined use of GPS and Galileo observations. The experimental data were collected from the Multi-GNSS Experiment network, covering the period of 2013–2015. The stability of both Galileo satellite and receiver DCBs over a time period of 36 months was thereby analyzed for the current state of the Galileo system. Good agreement of Galileo satellite DCBs is found between the IGGDCB-based DCB estimates and those from the German Aerospace Center (DLR), at the level of 0.22 ns. Moreover, high-level stability of the Galileo satellite DCB estimates is obtained over the selected time span (less than 0.25 ns in terms of standard deviation) by both IGGDCB and DLR algorithms. The Galileo receiver DCB estimates are also relatively stable for the case in which the receiver hardware device stays unchanged. It can also be concluded that the receiver DCB estimates are rather sensitive to the change of the firmware version and that the receiver antenna type has no great impact on receiver DCBs.

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

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others


  • Arikan F, Nayir H, Sezen U, Arikan O (2008) Estimation of single station interfrequency receiver bias using GPS-TEC. Radio Sci 43(4)

  • Bishop G, Walsh D, Daly P, Mazzella A, Holland E (1994) Analysis of the temporal stability of GPS and GLONASS group delay correction terms seen in various sets of ionospheric delay data. In: Proceedings of the 7th international technical meeting of the Satellite Division of The Institute of Navigation (ION GPS 1994), pp 1653–1661

  • Brunini C, Azpilicueta F (2010) GPS slant total electron content accuracy using the single layer model under different geomagnetic regions and ionospheric conditions. J Geod 84(5):293–304. doi:10.1007/s00190-010-0367-5

    Article  Google Scholar 

  • Ciraolo L, Azpilicueta F, Brunini C, Meza A, Radicella S (2007) Calibration errors on experimental slant total electron content (TEC) determined with GPS. J Geod 81(2):111–120

    Article  Google Scholar 

  • Coker C (1991) Variability of GPS satellite differential group delay biases. IEEE Trans Aerospace Electron Syst 27(6):931–938

    Article  Google Scholar 

  • Conte JF, Azpilicueta F, Brunini C (2011) Accuracy assessment of the GPS-TEC calibration constants by means of a simulation technique. J Geod 85(10):707–714. doi:10.1007/s00190-011-0477-8

    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. doi:10.1002/rds.20011

    Article  Google Scholar 

  • CSNO (2013) BeiDou navigation satellite system signal in space interface control document-open service signal (version 2.0)

  • Durmaz M, Karslioglu MO (2015) Regional vertical total electron content (VTEC) modeling together with satellite and receiver differential code biases (DCBs) using semi-parametric multivariate adaptive regression B-splines (SP-BMARS). J Geod 89(4):347–360. doi:10.1007/s00190-014-0779-8

    Article  Google Scholar 


  • Gao Y, Lahaye F, Heroux 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 

  • Guo F, Zhang X, Wang J (2015) Timing group delay and differential code bias corrections for BeiDou positioning. J Geod 89(5):427–445

    Article  Google Scholar 

  • Hernández-Pajares M (2004) IGS ionosphere WG status report: performance of IGS ionosphere TEC maps-position paper. In: IGS workshop, Bern

  • 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. doi:10.1007/s00190-008-0266-1

    Article  Google Scholar 

  • IS-GPS-200 (2012) Navstar GPS space segment/navigation user segment interfaces (IS-GPS-200, revision G). Glob Position Syst Direct

  • Jee G, Lee HB, Kim Y, Chung JK, Cho J (2010) Assessment of GPS global ionosphere maps (GIM) by comparison between CODE GIM and TOPEX/Jason TEC data: ionospheric perspective. J Geophys Res Space Phys 115(A10)

  • Keshin M (2012) A new algorithm for single receiver DCB estimation using IGS TEC maps. GPS Solut 16(3):283–292

    Article  Google Scholar 

  • Komjathy A (1997) Global ionospheric total electron content mapping using the Global Positioning System, University of New Brunswick

  • Komjathy A, Sparks L, Wilson BD, Mannucci AJ (2005) Automated daily processing of more than 1000 ground-based GPS receivers for studying intense ionospheric storms. Radio Sci 40(6)

  • Kouba J (2009) A guide to using International GNSS Service (IGS) products

  • Kozlov D, Tkachenko M, Tochilin A (2000) Statistical characterization of hardware biases in GPS\(+\) GLONASS receivers. In: Proceedings of the 13th international technical meeting of the Satellite Division of The Institute of Navigation (ION GPS 2000), pp 817–826

  • Lanyi GE, Roth T (1988) A comparison of mapped and measured total ionospheric electron content using global positioning system and beacon satellite observations. Radio Sci 23(4):483–492

    Article  Google Scholar 

  • Leandro RF, Langley RB, Santos MC (2007) Estimation of P2–C2 biases by means of precise point positioning. In: Proceedings of the ION 63rd annual meeting, Massachusetts, pp 225–231

  • 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. doi:10.1007/s00190-012-0565-4

    Article  Google Scholar 

  • Li Z, Yuan Y, Fan L, Huo X, Hsu H (2014) Determination of the differential code bias for current BDS satellites. IEEE Trans Geosci Remote Sensing 52(7):3968–3979. doi:10.1109/tgrs.2013.2278545

    Article  Google Scholar 

  • Li Z, Yuan Y, Wang N, Hernandez-Pajares M, Huo X (2014) SHPTS: towards a new method for generating precise global ionospheric TEC map based on spherical harmonic and generalized trigonometric series functions. J Geod. doi:10.1007/s00190-014-0778-9

  • 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. doi:10.1029/97rs02707

    Article  Google Scholar 

  • Mayer C, Becker C, Jakowski N, Meurer M (2011) Ionosphere monitoring and inter-frequency bias determination using Galileo: first results and future prospects. Adv Space Res 47(5):859–866

    Article  Google Scholar 

  • Montenbruck O, Hauschild A (2013) Code biases in multi-GNSS point positioning. In: Proceedings of ION ITM616-628

  • Montenbruck O, Steigenberger P (2013) The BeiDou navigation message. J Glob Position Syst 12(1):1–12

    Article  Google Scholar 

  • Montenbruck O, Hauschild A, Steigenberger P (2014) Differential code bias estimation using multi-GNSS observations and global ionosphere maps. In: Proceedings of the 2014 international technical meeting of the Institute of Navigation, pp 802–812

  • Montenbruck O, Steigenberger P, Khachikyan R, Weber G, Langley R, Mervart L, Hugentobler U (2014) IGS-MGEX: preparing the ground for multi-constellation GNSS science. Inside GNSS 9(1):42–49

    Google Scholar 

  • Mylnikova A, Yasyukevich YV, Kunitsyn V, Padokhin A (2015) Variability of GPS/GLONASS differential code biases. Results in Physics, pp 59–10

  • OS-SIS (2010) European GNSS (Galileo) open service signal in space interface control document(OS SIS ICD, issue 1.1). European Union

  • Øvstedal O (2002) Absolute positioning with single-frequency GPS receivers. GPS Solut 5(4):33–44

    Article  Google Scholar 

  • Pagny R, Dardelet J-C, Chenebault J (2005) From EGNOS to Galileo: a European vision of satellite-based radio navigation. In: Annales des télécommunications. Springer, pp. 357-375

  • Rao GS (2007) GPS satellite and receiver instrumental biases estimation using least squares method for accurate ionosphere modelling. J Earth Syst Sci 116(5):407–411

    Article  Google Scholar 

  • Rizos C, Montenbruck O, Weber R, Weber G, Neilan R, Hugentobler U (2013) The IGS MGEX experiment as a milestone for a comprehensive multi-GNSS service. In: Proceedings of ION PNT

  • 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 

  • 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(3):577–586

    Article  Google Scholar 

  • Schaer S (1999) Mapping and predicting the Earth’s ionosphere using the global positioning system

  • Shi C, Gu S, Lou Y, Ge M (2012) An improved approach to model ionospheric delays for single-frequency precise point positioning. Adv Space Res 49(12):1698–1708

    Article  Google Scholar 

  • Shi C, Yi W, Song W, Lou Y, Yao Y, Zhang R (2013) GLONASS pseudorange inter-channel biases and their effects on combined GPS/GLONASS precise point positioning. GPS Solut 17(4):439–451. doi:10.1007/s10291-013-0332-x

    Article  Google Scholar 

  • Shi C, Fan L, Li M, Liu Z, Gu S, Zhong S, Song W (2015) An enhanced algorithm to estimate BDS satellite’s differential code biases. J Geod. doi:10.1007/s00190-015-0863-8

  • Sunehra D (2013) Validation of GPS receiver instrumental bias results for precise navigation. Indian J Radio Space Phys 42:175–181

    Google Scholar 

  • Wang N, Yuan Y, Li Z, Montenbruck O, Tan B (2015) Determination of differential code biases with multi-GNSS observations. J Geod

  • Wanninger L (2012) Carrier-phase inter-frequency biases of GLONASS receivers. J Geod 86(2):139–148. doi:10.1007/s00190-011-0502-y

    Article  Google Scholar 

  • Warnant R (1997) Reliability of the TEC computed using GPS measurements—the problem of hardware biases. Acta Geod Geophys Hung 32(3–4):451–459

    Google Scholar 

  • Wilson B, Mannucci AJ (1993) Instrumental biases in ionospheric measurements derived from GPS data

  • Xue J, Song S, Zhu W (2015) Estimation of differential code biases for Beidou navigation system using multi-GNSS observations: how stable are the differential satellite and receiver code biases? J Geod. doi:10.1007/s00190-015-0874-5

  • Yasyukevich YV, Mylnikova A, Kunitsyn V, Padokhin A (2015) Influence of GPS/GLONASS differential code biases on the determination accuracy of the absolute total electron content in the ionosphere. Geomagn Aeronomy 55(6):763–769

    Article  Google Scholar 

  • Yasyukevich YV, Mylnikova AA, Kunitsyn VE, Padokhin AM (2015) Estimation of GPS/GLONASS differential code biases and their long-time variations

  • Yuan Y, Li Z, Wang N, Zhang B, Li H, Li M, Huo X, Ou J (2015) Monitoring the ionosphere based on the Crustal Movement Observation Network of China. Geod Geodyn 6(2):73–80. doi:10.1016/j.geog.2015.01.004

    Article  Google Scholar 

  • Yuan YB, Ou JK (1999) The effects of instrumental bias in GPS observations on determining ionospheric delays and the methods of its calibration. Acta Geodaetica et Cartographica Sinica 38:110–114

    Google Scholar 

  • Yuan YB, Ou JK (2004) A generalized trigonometric series function model for determining ionospheric delay. Prog Nat Sci 14(11):1010–1014. doi:10.1080/10020070412331344711

    Article  Google Scholar 

  • Yuan YB, Huo XL, Ou JK (2007) Models and methods for precise determination of ionospheric delay using GPS. Prog Nat Sci 17(2):187–196

    Article  Google Scholar 

  • Zhang BC, Ou JK, Yuan YB, 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. doi:10.1007/s11430-012-4454-8

    Article  Google Scholar 

  • Zhang BC, Teunissen PJ (2015) Characterization of multi-GNSS between-receiver differential code biases using zero and short baselines. Sci Bull 60(21):1840–1849

    Article  Google Scholar 

  • Zhang DH, Zhang W, Li Q, Shi LQ, Hao YQ, Xiao Z (2010) Accuracy analysis of the GPS instrumental bias estimated from observations in middle and low latitudes. Ann Geophys Germany 28(8):1571–1580. doi:10.5194/angeo-28-1571-2010

    Article  Google Scholar 

  • Zhang DH, Shi H, Jin YQ, Zhang W, Hao YQ, Xiao Z (2013) The variation of the estimated GPS instrumental bias and its possible connection with ionospheric variability. Sci China Technol Sci 57(1):67–79. doi:10.1007/s11431-013-5419-7

    Article  Google Scholar 

  • Zhang H, Gao Z, Ge M, Niu X, Huang L, Tu R, Li X (2013) On the convergence of ionospheric constrained precise point positioning (IC-PPP) based on undifferential uncombined raw GNSS observations. Sensors. 13(11):15708–15725

    Article  Google Scholar 

Download references


We would like to acknowledge the IGS Multi-GNSS Experiment (MGEX) and German Aerospace Center (DLR) for providing access to GNSS data and differential code bias (DCB) products. This work was supported by the National key Research Program of China “Collaborative Precision Positioning Project” (No.2016YFB0501900), China Natural Science Funds (No. 41674022, 41231064, 41304034, 41674043, 41621063, 41574033, 41321063, and 41504035), the National High-tech R&D Program of China (863 Program 2014AA123503), and the CAS/SAFEA International Partnership Program for Creative Research Teams (KZZD-EW-TZ-05).

Author information

Authors and Affiliations


Corresponding authors

Correspondence to Min Li or Yunbin Yuan.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, M., Yuan, Y., Wang, N. et al. Estimation and analysis of Galileo differential code biases. J Geod 91, 279–293 (2017).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: