Preliminary Results from the GPS/MET Atmospheric Remote Sensing Experiment

Feng, D.; Herman, Benjamin M.; Exner, Michael; Schreiner, William S.; McCloskey, Rick; Hunt, Doug

doi:10.1007/978-3-642-80133-4_22

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…For this purpose we used our clock estimates based on the IGS network. We processed data of GPS/MET, a LEO in a circular orbit about 750 km above the surface of the Earth (Feng et al, 1995). For the first results we sampled the 10-second data and used only 30-second data to have the same epochs as our highrate satellite clocks.…”

Section: Application To Leo Orbit Determinationmentioning

confidence: 99%

Processing aspects related to permanent GPS arrays

et al. 2014

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Preprocessing is an essential aspect for zero-and double-difference GPS software packages. In the first case we have to produce "clean" code and phase observations on the single receiver and single satellite level, in the second case solely double-difference observations have to be checked. The checks usually are performed on the "minimum constellation" level, i.e., the single receiver level for zero-, the single baseline level for double-difference packages. When analyzing the code observations stemming from a permanent array, this step may be performed in a much more efficient and robust way because the known geometry and, if available, the known atmospheric delays may be removed from the original observations. In an array of n receivers observing m satellites this leaves us with n · m observations and n + m − 1 unknowns (the clock parameters relative to a reference clock). The degree of freedom of f = n · m − (n + m − 1) (for, e.g., n = 10 and m = 10, we have f = 81) allows for a very robust detection of outliers and enables generating a satellite clock file based on code measurements (with very much reduced multipath and noise characteristics). A similar step may be performed with the differences of phase observations between subsequent epochs. Using an analogous procedure as in the case of code observations we may generate phase files with all cycle slips flagged or, in the case of "small-area" arrays, even with cycle slips repaired. Both steps, phase and code cleaning, are performed in the same program unit. We discuss this new development and present first results and applications using data from the AGNES (Automated GPS Network Switzerland) and the IGS (International GPS Service) Networks.

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Section: Application To Leo Orbit Determinationmentioning

confidence: 99%

Processing aspects related to permanent GPS arrays

et al. 2014

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Three months of continuous monitoring of atmospheric water vapor with a network of Global Positioning System receivers

Emardson¹,

Elgered²,

Johansson³

1998

J. Geophys. Res.

182

100

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Abstract. Three months of continuous data from the Global Positioning System (GPS) using 20 sites in Sweden and 5 sites in Finland have been used to estimate the integrated amount of atmospheric water vapor. The quality of the data has been assessed by comparisons with a microwave radiometer (water vapor radiometer (YVVR)) at the Onsala Space Observatory and with data from four different radiosonde stations. We found the agreement in integrated water vapor (IWV) between the GPS estimates and the radiometer data to be 1-2 kg/m 2 in terms of daily root-mean-square (rms) differences. A major part of these rms differences were caused by a bias between the data sets. This bias (WVR-GPS) varied from day to day between -1.0 and +2.5 kg/m 2 with a mean value of +1.3 kg/m 2.Comparisons with radiosonde data showed rms differences around or slightly above 2 kg/m 2 for each station using the entire 3 month data set. Also here the GPS estimates were, on the average, below the radiosonde results. We show that the radomes used to protect the GPS antennas are likely to cause a large part of the observed bias. Spatial structure functions were calculated by using the GPS and the radiosonde data. An overall consistency between the GPS-based and the radiosonde-based structure functions indicates that the spatial correlations between the GPS estimates are not affected by the estimation process used in the GPS data analysis.

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Preliminary Results from the GPS/MET Atmospheric Remote Sensing Experiment

Cited by 2 publications

References 4 publications

Processing aspects related to permanent GPS arrays

Processing aspects related to permanent GPS arrays

Three months of continuous monitoring of atmospheric water vapor with a network of Global Positioning System receivers

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