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IGS Orbit, Clock and EOP Combined Products: An Update

  • Jan Kouba
  • Yves Mireault
Part of the International Association of Geodesy Symposia book series (IAG SYMPOSIA, volume 118)

Abstract

Since January 1994 when the International GPS Service for Geodynamics (IGS) became an IAG service, several classes of IGS products have been generated on daily and weekly basis. IGS orbits, clocks and EOPs, based on weighted averages of the seven IGS Analysis Center (AC) daily solutions, are among these products. Throughout 1996 and 1997, a number of improvements, both in quality and product delivery times were realized resulting in enhanced quality of IGS combined products. The Final and Rapid orbit, clock and EOP delays were reduced significantly on June 30, 1996. Delays were reduced from one month to eleven days for the Final products and from eleven days to 24 hours for the Rapid products. New improved modeling and conventions, such as subdaily EOP modeling, ITRF94 and EOP rate solutions, were introduced on June 30, 1996 by all seven IGS ACs. These enhancements, along with the improved geometry of the IGS tracking network, resulted in steady orbit, clock and EOP solution improvements. The IGS combined orbit, clock and EOP products are currently approaching the 5 cm, 0.5 ns and 0.1 mas precision level respectively. Since March 1997, a new IGS orbit prediction product, also based on a weighted average, has been introduced. The new IGS orbit prediction is available in real-time and is significantly better than the broadcast GPS orbits. Typically, the IGS orbit prediction, when compared to the IGS Rapid orbits, is at or below the 1 metre precision level, while broadcast orbits compare at the 3–5m RMS level. Also, in March 1997, a new IGS LOD/UT1 combination based on a weighted average of AC LOD solutions was officially introduced. Encouraging results were obtained and are presented hereafter.

Keywords

Analysis Center Polar Motion Earth Orientation Parameter Broadcast Orbit Orbit Prediction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Jan Kouba
    • 1
  • Yves Mireault
    • 1
  1. 1.Geodetic Survey DivisionNatural Resources CanadaOttawaCanada

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