REFAG 2014 pp 39-46 | Cite as

The Processing of Single Differenced GNSS Data with VLBI Software

  • Younghee Kwak
  • Johannes Böhm
  • Thomas Hobiger
  • Lucia Plank
Conference paper
Part of the International Association of Geodesy Symposia book series (IAG SYMPOSIA, volume 146)


Space geodetic techniques such as Very Long Baseline Interferometry (VLBI) and Global Navigation Satellite Systems (GNSS) are used for the determination of celestial and terrestrial reference frames and Earth orientation parameters. It is potentially valuable to combine the observations from the different techniques to fully exploit the strengths and unique characteristics of the techniques. Today, discrepancies of locally measured ties between reference points of two techniques and the space geodesy results are a potential issue in the determination of reference frames. To improve the link between the techniques, tests are under way to observe GNSS signals with VLBI radio telescopes directly, and to observe GNSS signals in GNSS antennas with subsequent processing in the VLBI system (“GNSS-VLBI Hybrid System”) including VLBI correlation. In both cases, the GNSS data type is the difference in travel time from the satellite to two ground stations. However, it is still difficult to acquire those observations and thus we apply post-processed phase measurements from a precise point positioning (PPP) solution with the c5++ software to build those difference values which are then used in the Vienna VLBI Software (VieVS). We take seven GNSS sites, exclusively Global Positioning System (GPS) in this study, co-located with CONT11 VLBI sites to validate the models in VieVS for single differenced GNSS data, and estimate geodetic parameters. We find root mean square values of post-fit residuals for the VLBI-like observations of about 3.3 cm, compared to less than 2.0 cm from the GNSS PPP solution. At this stage, we do also find degradation in station coordinate repeatabilities (by a factor of 2 to 8), which is related to the systematic residuals.


Combination at the observation level GNSS GNSS-VLBI hybrid system VLBI 



We thank the three anonymous reviewers and the associate editor for their helpful comments and suggestions. This work has been supported by project Hybrid GPS-VLBI (M1592) which is funded by the Austrian Science Fund (FWF) and Fellowship FS1000100037 of the Australian Research Council.


  1. Böhm J, Werl B, Schuh H (2006) Troposphere mapping functions for GPS and very long baseline interferometry from European centre for medium-range weather forecasts operational analysis data. J Geophys Res 111:B02,406. doi:10.1029/2005JB003629 Google Scholar
  2. Böhm J, Heinkelmann R, Schuh H (2007) Short note: a global model of pressure and temperature for geodetic applications. J Geod 81(10):679–683. doi:10.1007/s00190-007-0135-3 CrossRefGoogle Scholar
  3. Böhm J, Böhm S, Nilsson T, Pany A, Plank L, Spicakova H, Teke K, Schuh H (2012) The new Vienna VLBI software VieVS. In: Kenyon S, Pacino MC, Marti U (eds) Geodesy for planet earth, international association of geodesy symposia, vol 136. Springer, Berlin/Heidelberg, pp 1007–1011. doi:10.1007/978-3-642-20338-1-126 Google Scholar
  4. Haas R, Neidhardt A, Kodet J, Plötz C, Schreiber U, Kronschnabl G, Pogrebenko S, Duev D, Casey S, Marti-Vidal I, Yang J, Plank L (2014) The Wettzell-Onsala G130128 experiment VLBI-observations of a GLONASS satellite. In: D DB, Baver K, Armstrong K (eds) IVS 2014 general meeting proceedings. Science Press, BeijingGoogle Scholar
  5. Hellerschmied A, Böhm J, Plank L, Neidhardt A, Kodet J, Haas R (2015) Scheduling VLBI observations to satellites with VieVS. In: Proceedings of IAG Commission 1 Symposium 2014. doi:10.1007/427751_1_En_183Google Scholar
  6. Hobiger T, Otsubo T (2014) Combination of GPS and VLBI on the observation level during CONT11 – common parameters, ties and inter-technique biases. J Geod 88(11):1017–1028. doi:10.1007/s00190-014-0740-x CrossRefGoogle Scholar
  7. Kwak Y, Kondo T, Gotoh T, Amagai J, Takiguchi H, Sekido M, Ichikawa R, Sasao T, Cho J, Kim T (2011) Validation experiment of the GPS-VLBI hybrid system. In: Alef W, Bernhart S, Nothnagel A (eds) Proceedings of the 20th EVGA meeting, pp 154–157Google Scholar
  8. Lyard F, Lefevre F, Letellier T, Francis O (2006) Modelling the global ocean tides: modern insights from FES2004. Ocean Dyn 56:394–415. doi:10.1007/s10236-006-0086-x CrossRefGoogle Scholar
  9. Petit G, Luzum B (2010) IERS Conventions (2010). IERS technical note 36. Verlag des Bundesamtes fü Kartographie und GeodäsieGoogle Scholar
  10. Plank L, Böhm J, Madzak M, Tierno Ros C, Schuh H (2012) Processing SELENE differential VLBI data. In: D DB, Baver K (eds) IVS 2012 General meeting proceedings, NASA/CP-2012-217504, pp 291–295Google Scholar
  11. Plank L, Böhm J, Krasna H, Schuh H (2013) VLBI satellite tracking for precise coordinate determination: a simulation study. In: Zubko N, Poutanen M (eds) Proceedings of the 21st meeting of the European VLBI group for geodesy and astronomy, Reports of the Finnish Geodetic Institute, pp 105–109Google Scholar
  12. Plank L, Böhm J, Schuh H (2014) Precise station positions from VLBI observations to satellites: a simulation study. J Geod 88:659–673. doi:10.1007/s00190-014-0712-1 CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Younghee Kwak
    • 1
  • Johannes Böhm
    • 1
  • Thomas Hobiger
    • 2
  • Lucia Plank
    • 3
  1. 1.Vienna University of TechnologyViennaAustria
  2. 2.Department of Earth and Space Science, Chalmers University of TechnologyOnsala Space ObservatoryOnsalaSweden
  3. 3.University of TasmaniaHobartAustralia

Personalised recommendations