Project P9 Usability of timevariable Earth orientation parameters and gravity field coefficients fro

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IGS Analysis Center Workshop, 2-6 June 2008,
Florida, USA
GPS in the ITRF Combination
D. Angermann, H. Drewes, M. Krügel, B. Meisel
Deutsches Geodätisches Forschungsinstitut,
München E-Mail angermann_at_dgfi.badw.de
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Outline

• ITRS Combination Center at DGFI
• Input data for TRF computations
• Analysis and accumulation of GPS time series
• GPS in the inter-technique combination
• Contribution of GPS to the datum realization
• Conclusions and outlook

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ITRS Combination Center at DGFI

• General concept Combination on the normal
  equation level
• Software DGFI Orbit and Geodetic Parameter
  Estimation
• Software (DOGS)

Geodetic datum
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Input data sets for TRF computations (1/2)
ITRF2005 Time series of station positions and EOP

• ITRF2005 data sets are not fully consistent, the
  standards and
• models were not completely unified among analysis
  centers
• Shortcomings concerning GPS
• IGS solutions are not reprocessed (e.g., model
  and software changes)
• Relative antenna phase center corrections were
  applied

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Input data sets for TRF computations (2/2)
GGOS-D Time series of station positions and EOP

• Improvements of GGOS-D data compared to ITRF2005
• Homogeneously processed data sets
• - Identical standards, conventions, models,
  parameters
• - GPS PDR (Steigenberger et al. 2006, Rülke
  et al. 2008)
• Improved modelling
• - for GPS absolute instead of relative
  phase centre corr.
• - for VLBI pole tide model was changed

GGOS-D German project of BKG, DGFI, GFZ and IGG
funded by BMBF
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TRF computation strategy

• First step Analysis of station coordinate time
  series and computation of a reference frame per
  technique
• Modelling time dependent station coordinates by
• epoch positions
• linear velocities
• - (seasonal signals)
• - discontinuities

Second step Combination of different techniques
by - relative weighting - selection of
terrestrial difference vectors (local ties) -
combination of station velocities and EOP -
realization of the geodetic datum
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TRF per technique (1/4)
Analysis of GPS station position time series
Instrumentation changes
Earthquakes Seasonal variations
ITRF2005. 221 discontinuities in 332 GPS stations
(1996 - 2005) GGOS-D 95 discontinuities in
240 GPS stations (1994 - 2007)
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TRF per technique (2/4)
Effect of annual signals ?
Equating of station velocities ?
1997 2000
2003 2006
1997 2000
2003 2006
Sol. ID 1
Sol. ID 2
GPS station Irkutsk (Siberia)
GPS station Hofn (Iceland)
Velocity differences w.r.t. a linear model
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TRF per technique (3/4)
Seasonal signals - Comparison with geophysical
data
cm
2 0 -2
Models consider atmospheric, oceanic and
hydrologic mass loads NCEP, ECCO, GLDAS
Potsdam
Correlation coefficient 0,50
2 0 -2
Krasnoyarsk
Correlation coefficient 0,79
2 0 -2
Bahrain
Correlation coefficient 0,73
1997 1999 2 001
2003 2005
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TRF per technique (4/4)
Shape of seasonal signals can be approximated by
sine/cosine annual and semi-annual functions
Brasilia
Ankara
Estimation of annual signals in addition to
velocities ?

• Disadvantages / open questions
• More parameters (stability) ?
• Seasonal signal geophysically meaningful ?
• How to parameterize seasonal signals ?

• Advantages
• Improved velocity estimation
• Better alignment of epoch solutions

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Computation of the TRF (1/3)
Selection of local ties at co-location sites
SLR-VLBI (9)
SLR-GPS (25)
VLBI-GPS (27)
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Computation of the TRF (2/3)
Selection of terrestrial difference vectors
(1) Three-dimensional differences between space
geodetic solutions (GPS and VLBI) and terrestrial
difference vectors mm
ITRF2005 GGOS-D
stations in southern hemisphere
Krügel et al. 2007 Poster presented at AGU Fall
Meeting 2007
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Computation of the TRF (3/3)
Selection of terrestrial difference vectors (2)
Mean pole difference
Mean pole difference 35 mas (1 mm) Network
deformation 0.3 mm Number of co-locations
19 ITRF2005 Pole difference 41
mas Deformation 1.0 mm No. co-locations
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Network deformation
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Realization of the geodetic datum (1/4)
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Realization of the geodetic datum (2/4)
Station velocity residuals for 56 core stations
used to realize the kinematic datum of the
ITRF2005D solution w.r.t. APKIM
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Realization of the geodetic datum (3/4)
Translation and scale estimates of similarity
transformations between combined PDR05 and
weekly solutions (Rülke et al., JGR 2008)
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Realization of the geodetic datum (4/4)
Datum information of GPS observations (compared
to SLR)
Cdatum (GT CGPS-1 G)-1
Method
CGPS Covariance matrix of GPS solution (loose
constrained) G Coefficients of 7 parameter
similarity transformation matrix Cdatum Covarianc
e matrix of datum parameters
Standard deviations for datum parameters mm
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Conclusions and outlook

• Discontinuities Number of jumps reduced due to
  homogeneous re- processing discontinuity tables
  among techniques should be adjusted.
• Annual signals Treatment of seasonal variations
  in station positions (e.g., by estimating
  sine/cosine functions) should be investigated.
• Co-locations Discontinuities are critical at
  least two GPS instruments should be operated at
  each co-location site.
• Geodetic datum GPS reprocessing provides stable
  results for the scale and for the x- and
  y-component of the origin, the z-component shows
  large seasonal variations which should be
  investigated.
• GPS reprocessing is essential for the next ITRF
  (unified standards and models should be applied
  for different techniques).