Global Navigation Satellite Systems (GNSS) are based on measuring the time that elapses between the signal’s transmission at the satellite and its reception on the ground. Therefore, clock information is required on both sides. While the GNSS satellites are equipped with atomic clocks, ground stations usually use the time information from the internal oscillator of their GNSS receiver, which has a much lower time-keeping performance compared to the satellite clocks. Nevertheless, some continuously operated tracking stations obtain their time information from an external atomic clock, as it is the case with many stations of the International GNSS Service (IGS). To compensate for synchronization errors, current GNSS analysis models generally introduce clock biases for satellites and receivers into the observation equations. The often-made assumption of a pure white noise behavior for the estimated clocks may lead to high correlations with other geodetic parameters, such as the radial orbit error for the satellite clock, or the station height coordinate and tropospheric delay parameters for the station clock. A general solution to this problem is to reduce the amount of unknown clock parameters by modeling them in the adjustment process. In order to be modeled adequately, the corresponding clock must have a high degree of stability, which is particularly crucial for the ground stations. In this contribution, we investigate the clock stability of globally distributed IGS tracking stations. Those IGS stations, that are steered by an external Hydrogen-Maser (H-Maser) clock, are considered in a global network analysis over a period of several weeks. The generated clock products are used to compare the frequency stabilities within the station network, as well as with the mean behavior of GPS and Galileo satellite blocks. After some further research on stations with significantly higher deviations, the final result of this contribution will be a set of reliable ground stations, that will serve as a basis for future clock modeling approaches at GFZ.
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Widczisk et al. (2024) studied this question.
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