Abstract
Various studies have been performed to investigate the accuracy of troposphere zenith wet delays (ZWDs) determined from GPS. Most of these studies use dual-frequency GPS data of large-scale networks with long baselines to determine the absolute ZWDs. For small-scale networks the estimability of the absolute ZWDs deteriorates due to high correlation between the solutions of the ZWDs and satellite-specific parameters as satellite clocks. However, as relative ZWDs (rZWDs) can always be estimated, irrespective of the size of the network, it is of interest to understand how the large-scale network rZWD-performance of dual-frequency GPS using an ionosphere-float model compares to the small-scale network rZWD-performance of single-frequency GPS using an ionosphere-weighted model. In this contribution such an analysis is performed using undifferenced and uncombined network parametrization modelling. In this context we demonstrate the ionosphere weighted constraints, which allows the determination of the rZWDs independent from signals on the second frequency. Based on an analysis of both simulated and real data, it is found that under quiet ionosphere conditions, the accuracy of the single-frequency determined rZWDs in the ionosphere-weighted network is comparable to that of the large-scale dual-frequency network without ionospheric constraints. Making use of the real data from two baselines of 15 days, it was found that the absolute differences of the rZWDs applying the two strategies are within 1 cm in over 90% and 95% of the time for ambiguity-float and -fixed cases, respectively.
Highlights
Can always be estimated, irrespective of the size of the network, it is of interest to understand how the large-scale network rZWD-performance of dual-frequency Global Positioning System (GPS) using an ionosphere-float model compares to the small-scale network rZWD-performance of single-frequency GPS using an ionosphere-weighted model. In this contribution such an analysis is performed using undifferenced and uncombined network parametrization modelling. In this context we demonstrate the ionosphere weighted constraints, which allows the determination of the rZWDs independent from signals on the second frequency
Making use of the real data from two baselines of 15 days, it was found that the absolute differences of the rZWDs applying the two strategies are within 1 cm in over 90% and 95% of the time for ambiguity-float and -fixed cases, respectively
GNSS meteorology (Bevis et al 1992) provides the possibility to retrieve the temporal and spatial variation of the precipitable water vapour (PWV) and as such is an alternative to other techniques such as radiosondes (Coster et al 1996), water vapour radiometer (WVR) (Gradinarsky and Elgered 2000), very long baseline interferometry (VLBI) (Coster et al 1996; Niell et al 2001) and Doppler orbitography radiopositioning integrated by satellite (DORIS)
Summary
GNSS meteorology (Bevis et al 1992) provides the possibility to retrieve the temporal and spatial variation of the precipitable water vapour (PWV) and as such is an alternative to other techniques such as radiosondes (Coster et al 1996), water vapour radiometer (WVR) (Gradinarsky and Elgered 2000), very long baseline interferometry (VLBI) (Coster et al 1996; Niell et al 2001) and Doppler orbitography radiopositioning integrated by satellite (DORIS) We keep all the information in the observational model and make use of the undifferenced and uncombined GPS observation equations (Odijk et al 2016), so that freedom is left for applying appropriate dynamic models for parameters that otherwise would have been eliminated We apply this approach to two type of networks, a DF large-scale network in which no information about the ionospheric delays is provided, and a SF small-scale network based on an ionosphere-weighted model, i.e., in which stochastic spatial constraints are placed on the differential ionospheric delays. The absolute ZWD solutions become poorly estimable (Odijk et al 2016) They are often estimated in large-scale networks including baselines longer than 500 km (Rocken et al 1995) or more (Tregoning et al 1998).
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