Some tests of wet tropospheric calibration for the CASA Uno Global Positioning System Experiment

Abstract

Wet tropospheric path delay can be a major error source for Global Positioning System (GPS) geodetic experiments. We investigate strategies for minimizing this error using data from CASA Uno, the first major GPS experiment in Central and South America, where wet path delays may be both high and variable. We compared wet path delay calibration using water vapor radiometers (WVRs) and residual delay estimation, with strategies where the entire wet path delay is estimated stochastically without prior calibration, using data from a 270 km test baseline in Costa Rica. Both approaches yield centimeter‐level baseline repeatability and similar tropospheric estimates, suggesting that WVR calibration is not critical for obtaining high precision results with GPS in the CASA region.

Crustal deformation measurements using repeat‐pass JERS 1 synthetic aperture radar interferometry near the Izu Peninsula, Japan

“…Second, differential atmospheric delay biases the phase measurement. The effect of water vapor in the atmosphere is well known from microwave space geodetic techniques, such as very long baseline interferometry (VLI3I) [Herring, 1986] and GPS [Dixon and Wolf, 1990]. Goldstein [1995], Rosen et al [1996], and Zebker et al [1997] described the phase delay in the interferograms derived from SIR-C data but were limited to only a few observations of disparate sites.…”

Noise behavior in CGPS position time series: the eastern North America case study

“…In this case, while the variable white noise shows dependency on station latitude and the number of satellites used in the solution, the flicker noise amplitude does not show dependency on latitude. The regional correlations are attributed to mismodeling due to tropospheric water vapor Dixon and Kornreich Wolf (1990), the first-order ionospheric phase advance and group delay Montillet et al (2013) and the near polar satellites' orbit in the case of the DORIS time series Williams and Willis (2006).…”

Satellite Positioning

“…Instead, it is corrected using models of the lower atmosphere and site meteorological data; usually further corrections are estimated from the tracking data itself, to account for variations in the atmosphere not represented by the atmospheric models. A practical and effective approach is to treat these variations as outcomes of low‐order stochastic processes in sequential estimation procedures [Tralli et al, 1988, Tralli and Lichten, 1990, Dixon and Wolf, 1990]. Water vapor radiometer measurements could be used instead to calculate refraction directly, but there is no clear indication that this offers any significant advantage over the corrections just described, and such devices are very costly at present.…”