Reference : The Effect of Processing Technique and Reference Frame Definition on Noise in CGPS Po...
Scientific congresses, symposiums and conference proceedings : Poster
Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
The Effect of Processing Technique and Reference Frame Definition on Noise in CGPS Position Time Series
Teferle, Felix Norman mailto [University of Nottingham > Institute of Engineering Surveying and Space Geodesy]
Williams, Simon [Proudman Oceanography Laboratory]
Kierulf, Halfdan [Norwegian Mapping Agency]
Bingley, Richard [University of Nottingham > Institute of Engineering Surveying and Space Geodesy]
Plag, Hans-Peter [University of Nevada Reno > Nevada Geodetic Laboratory]
American Geophysical Union Fall Meeting 2005
5-12-2005 to 9-12-2005
American Geophysical Union
San Francisco, CA
[en] GPS processing ; coordinate time series analysis ; stochastic noise ; reference frame
[en] In this presentation we investigate the effects of GPS processing techniques and strategies, and the related reference frame realization, on the stochastic properties of continuous GPS (CGPS) position time series. It was of particular interest to establish whether and how different GPS processing techniques and strategies, e.g. double differencing (DD) and precise point positioning (PPP), and the use of different orbit and clock products, and/or the definition of the reference frame (partly dependent on the applied strategy) affect the colored noise content of time series. We used CGPS position time series from 15 different solutions obtained from seven different analysis centers as part of the European Sea Level Service - Research Infrastructure project (ESEAS-RI) using the GIPSY OASIS II, GAMIT and Bernese GPS softwares. All time series analyzed have at least three years of data for the period between 2000 and 2005. Furthermore, a selected set of position time series was also analyzed using Empirical Orthogonal Function (EOF) analysis. The noise content of the first 15 modes, representing the solution-specific common mode time series for each of the selected solutions were then also investigated for colored noise. Using Maximum Likelihood Estimation (MLE) a white, a white plus flicker, a white plus power- law and a white plus first-order Gauss-Markov (FOGM) noise model were fitted to the position and EOF time series data. For both the position and EOF time series the parameter model included a constant, a rate and harmonic terms with annual, semi-annual, 4- monthly, 3-monthly, 2.4-monthly and 13.66 day periods. Position jumps were modeled at logged epochs or at visible discontinuities in the time series. The MLE showed that in most cases the best fitting noise model is a combination of white plus power-law noise with average spectral indices in the range between -0.5 and -1.4. This model is closely followed by the combination of white plus flicker and white plus FOGM noise. The noise properties of the EOF time series follow predominantly a white plus power-law character, with the first few modes indicating a white plus flicker noise behavior. In general, DD solutions contain less noise than PPP solutions and that regional reference frame definitions further reduce the amount of noise in the time series.
EC Framework 5 Contract No. EVR1-CT- 2002-40025

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