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From March to August 1990, the signals transmitted by the Block II satellites of the GPS were dithered under a policy of 'Selective Availability' (SA). The dithering appears as an about 10 to the -10th deviation of the satellite oscillator frequency, which, when accumulated over several minutes, can produce an error of about 100 cycles in the model for carrier beat phase. Differencing between simultaneously sampling receivers minimizes the error. If, however, the receivers do not sample simultaneously, it is necessary to model the frequency deviation. Such a model is here applied to data collected in March 1990 by TI4100 and Minimac receivers sampling at times separated by 0.92 s. Applying the algorithm significantly improves the rms scatter of the estimated relative position vectors. The rms scatter from a data set including dithered satellites is similar for both simultaneously and nonsimultaneously sampling receivers, a result which indicates that SA can be adequately modeled.

[1] One major part in the error budget of GPS measurements is the imperfect modeling of the tropospheric delay. By processing a global network of 195 stations we have compared two different mapping techniques: (1) the commonly used Niell hydrostatic mapping function (NMF) and (2) the isobaric hydrostatic mapping function (IMF) based on numerical weather fields. The two solutions reveal significant differences in the derived zenith total delay (ZTD) parameters and site positions. The largest differences occur in Antarctica, where the annual mean heights differ by up to 15 mm. We infer that the significant differences are related to model deficiencies in NMF since a) IMF improves the repeatability in station heights in high southern latitudes significantly, and b) using IMF reduces the dependence of the solution on the elevation cut-off angle by about 20%. In conclusion, the use of mapping function (MF) parameters based on meteorological data is strongly recommended for global GPS analyses.

[1] In this paper we present results of a global gravity field recovery using half a year of CHAMP data. We use the energy integral of the motion of a satellite to transform satellite velocities into values of gravitational potential. The feasibility of this approach has already been demonstrated by several groups, using CHAMP reduced-dynamic orbits. We show, that the potential recovered from this kind of orbits depends on the a priori gravity field used for orbit determination. Thus, it cannot be excluded that errors present in the prior field propagate into the new CHAMP gravity model. It is the intention of this paper to avoid this dependency through the use of kinematic orbits, which are free from prior information. The derived potential model, TUM-1S, is validated by comparison to ground data and by satellite orbit residuals. It is shown to be comparable in quality to other state-of-the-art gravity field models.