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Journal of Geodesy

, Volume 86, Issue 1, pp 1–14 | Cite as

Strategies to mitigate aliasing of loading signals while estimating GPS frame parameters

  • Xavier CollilieuxEmail author
  • Tonie van Dam
  • Jim Ray
  • David Coulot
  • Laurent Métivier
  • Zuheir Altamimi
Original Article

Abstract

Although GNSS techniques are theoretically sensitive to the Earth center of mass, it is often preferable to remove intrinsic origin and scale information from the estimated station positions since they are known to be affected by systematic errors. This is usually done by estimating the parameters of a linearized similarity transformation which relates the quasi-instantaneous frames to a long-term frame such as the International Terrestrial Reference Frame (ITRF). It is well known that non-linear station motions can partially alias into these parameters. We discuss in this paper some procedures that may allow reducing these aliasing effects in the case of the GPS techniques. The options include the use of well-distributed sub-networks for the frame transformation estimation, the use of site loading corrections, a modification of the stochastic model by downweighting heights, or the joint estimation of the low degrees of the deformation field. We confirm that the standard approach consisting of estimating the transformation over the whole network is particularly harmful for the loading signals if the network is not well distributed. Downweighting the height component, using a uniform sub-network, or estimating the deformation field perform similarly in drastically reducing the amplitude of the aliasing effect. The application of these methods to reprocessed GPS terrestrial frames permits an assessment of the level of agreement between GPS and our loading model, which is found to be about 1.5 mm WRMS in height and 0.8 mm WRMS in the horizontal at the annual frequency. Aliased loading signals are not the main source of discrepancies between loading displacement models and GPS position time series.

Keywords

Loading effects Terrestrial Reference Frame GNSS GPS Geocenter motion 

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References

  1. Altamimi Z, Collilieux X, Legrand J, Garayt B, Boucher C (2007) ITRF2005: a new release of the International Terrestrial Reference Frame based on time series of station positions and Earth Orientation Parameters. J Geophys Res 112(B09401). doi: 10.1029/2007JB004949
  2. Altamimi, Z and Collilieux, X and Métivier, L (2011) ITRF2008: an improved solution of the International Terrestrial Reference Frame. J Geodesy. doi: 10.1007/s00190-011-0444-4
  3. Blewitt G (2003) Self-consistency in reference frames, geocenter definition, and surface loading of the solid Earth. J Geophys Res 108. doi: 10.1029/2002JB002082
  4. Blewitt G, Lavallée D (2000) Effect of annually repeating signals on geodetic velocity estimates. Tenth General Assembly of the WEGENER Project (WEGENER 2000), San Fernando, Spain, September 18–20Google Scholar
  5. Collilieux X, Altamimi Z, Coulot D, Ray J, Sillard P (2007) Comparison of very long baseline interferometry, GPS, and satellite laser ranging height residuals from ITRF2005 using spectral and correlation methods. J Geophys Res 112(B12403). doi: 10.1029/2007JB004933
  6. Collilieux X, Altamimi Z, Ray J, van Dam T, Wu X (2009) Effect of the satellite laser ranging network distribution on geocenter motion estimation. J Geophys Res 114(B04402). doi: 10.1029/2008JB005727
  7. Collilieux X, Altamimi Z, Coulot D, van Dam T, Ray J (2010) Impact of loading effects on determination of the International Terrestrial Reference Frame. Adv Space Res 45: 144–154. doi: 10.1016/j.asr.2009.08.024 CrossRefGoogle Scholar
  8. Collilieux X, Métivier L, Altamimi Z, van Dam T, Ray J (2010b) Quality assessment of GPS reprocessed Terrestrial Reference Frame. GPS Solut. doi: 10.1007/s10291-010-0184-6
  9. Farrell WE (1972) Deformation of the earth by surface loads. Rev Geophys Space Phys 10(3): 761–797CrossRefGoogle Scholar
  10. Fritsche M, Dietrich R, Rülke A, Rothacher M, Steigenberger P (2010) Low-degree earth deformation from reprocessed GPS observations. GPS Solut 14(2): 165–175. doi: 10.1007/s10291-009-0130-7 CrossRefGoogle Scholar
  11. Guo J, Ou J, Wang H (2010) Robust estimation for correlated observations: two local sensitivity-based downweighting strategies. J Geodesy 84(4): 243–250. doi: 10.1007/s00190-009-0361-y CrossRefGoogle Scholar
  12. Han D, Wahr J (1995) The viscoelastic relaxation of a realistically stratified earth, and a further analysis of postglacial rebound. Geophys J Int 120: 287–311. doi: 10.1111/j.1365-246X.1995.tb01819.x CrossRefGoogle Scholar
  13. Herring T (2004) GLOBK: Global Kalman filter VLBI and GPS analysis program version 4.1. Tech. rep., Massachusetts Institute of Technology, CambridgeGoogle Scholar
  14. Lavallée DA, van Dam TM, Blewitt G, Clarke PJ (2006) Geocenter motions from GPS: A unified observation model. J Geophys Res 111: 5405. doi: 10.1029/2005JB003784 CrossRefGoogle Scholar
  15. Mangiarotti S, Cazenave A, Soudarin L, Crétaux JF (2001) Annual vertical crustal motions predicted from surface mass redistribution and observed by space geodesy. J Geophys Res 106: 4277–4292. doi: 10.1029/2000JB900347 CrossRefGoogle Scholar
  16. McCarthy D, Petit G (2004) IERS Technical Note 32-IERS Conventions (2003). Tech. rep., Verlag des Bundesamts fur Kartographie und Geodasie, Frankfurt am Main, Germany. http://maia.usno.navy.mil/conv2003.html
  17. Petrov L, Boy J (2004) Study of the atmospheric pressure loading signal in very long baseline interferometry observations. J Geophys Res 109(B18). doi: 10.1029/2003JB002500
  18. Ray J, Altamimi Z, Collilieux X, van Dam TM (2008) Anomalous harmonics in the spectra of GPS position estimates. GPS solution 12(1): 55–64. doi: 10.1007/s10291-007-0067-7 CrossRefGoogle Scholar
  19. Rodell M, Houser PR, Jambor U, Gottschalck J, Mitchell K, Meng CJ, Arsenault K, Cosgrove B, Radakovich J, Bosilovich M, Entin JK, Walker JP, Lohmann D, Toll D (2004) The Global Land Data Assimilation System. Bull Amer Meteor Soc 85(3): 381–394. doi: 10.1175/BAMS-85-3-381 CrossRefGoogle Scholar
  20. Stammer D, Wunsch C, Fukumori I, Marshall J (2002) State estimation improves prospects for ocean research. Eos Trans AGU 83(27): 289–295. doi: 10.1029/2002EO000207 CrossRefGoogle Scholar
  21. Tregoning P, van Dam TM (2005) Effects of atmospheric pressure loading and seven-parameter transformations on estimates of geocenter motion and station heights from space geodetic observations. J Geophys Res 110: 3408. doi: 10.1029/2004JB003334 CrossRefGoogle Scholar
  22. van Dam TM, Herring TA (1994) Detection of atmospheric pressure loading using very long baseline interferometry measurements. J Geophys Res 99: 4505–5417. doi: 10.1029/93JB02758 CrossRefGoogle Scholar
  23. van Dam TM, Blewitt G, Heflin MB (1994) Atmospheric pressure loading effects on Global Positioning System coordinate determinations. J Geophys Res 99: 23939–23950. doi: 10.1029/94JB02122 CrossRefGoogle Scholar
  24. van Dam TM, Wahr J, Milly PCD, Shmakin AB, Blewitt G, Lavallée D, Larson KM (2001) Crustal displacements due to continental water loading. Geophys Res Lett 28: 651–654. doi: 10.1029/2000GL012120 CrossRefGoogle Scholar
  25. Wessel P, Smith WHF (1991) Free software helps map and display data. EOS Trans 72: 441. doi: 10.1029/90EO00319 CrossRefGoogle Scholar
  26. Wu X, Argus DF, Heflin MB, Ivins ER, Webb FH (2002) Site distribution and aliasing effects in the inversion for load coefficients and geocenter motion from GPS data. Geophys Res Lett 29(24): 2210. doi: 10.1029/2002GL016324 CrossRefGoogle Scholar
  27. Wu X, Heflin MB, Ivins ER, Argus DF, Webb FH (2003) Large-scale global surface mass variations inferred from GPS measurements of load-induced deformation. Geophys Res Lett 30(14): 1742. doi: 10.1029/2003GL017546 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Xavier Collilieux
    • 1
    Email author
  • Tonie van Dam
    • 2
  • Jim Ray
    • 3
  • David Coulot
    • 1
  • Laurent Métivier
    • 1
    • 4
  • Zuheir Altamimi
    • 1
  1. 1.IGN/LAREG et GRGSMarne La Vallée Cedex 2France
  2. 2.University of LuxembourgLuxembourgLuxembourg
  3. 3.NOAA National Geodetic SurveySilver SpringUSA
  4. 4.Institut de Physique du Globe de ParisParisFrance

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