# A New Online Service for the Validation of Multi-GNSS Orbits Using SLR
## 3 Results
### Assessment of the Orbit Quality
Mean offsets for FOC, FOC\({}^{*}\), IOV, K1, M satellites are smaller for single-photon stations equipped with CSPAD detectors in comparison to multi-photon stations equipped with MCP or PMT detectors. For instance, the mean offset equals \(-36\)\(\pm\) 41, \(-43\)\(\pm\) 36, and \(-44\)\(\pm\) 39 for Galileo FOC and \(-3\)\(\pm\) 27, \(-20\)\(\pm\) 20, and \(-6\)\(\pm\) 31 for GLONASS-K1, for CSPAD, MCP, and PMT detectors, respectively. The MCP and the PMT stations are more vulnerable to satellite signature effect [33; 50; 54], hence the dependency on the incident angle should be larger and negative (see Figure 5). The histograms of SLR residuals to GNSS for selected MCP and PMT stations are asymmetrical (see Figure 6). The histograms are broader on the left side creating some form of a tail, which may confirm that MCP and PMT detectors are affected by the satellite signature effect. The multi-photon detectors are not able to register full range of returning photons. For high incidence angles, many of registered photons return after the reflection from the nearest edge of the flat LRA. The core statistics for TOP10 stations are very similar to the dataset containing all stations, however, the standard deviation decreases, especially for GLONASS satellites: 26 to 21, 36 to 26 and 28 to 24 mm, for K1, M and M+, respectively. Some of the most efficient Russian laser stations such as 1868 Komsomsolsk, 1887 Baikonur, or 1886 Arkhyz indicate inexplicable range bias or a high value of the standard deviation. The laser stations in Shanghai 7821 and Changchun 7827 show a dependency between the values of SLR residuals and the elevation angle of performed observation (see Table A1). Such biases and dependencies may affect the validation results as in the case of abovementioned comparison. Further statistics related to the particular stations are attached in the Table A1 where three types of characteristics are shown: (1) general statistics including the mean, median and standard deviation of the SLR residuals, as well as the number of observations; (2) dependency between SLR residuals and the nadir angle; and (3) dependency between SLR residuals and the elevation angle. Statistics for different types of satellites differ even within the same satellite system (see Table 3, TOP10). The mean offset for Galileo FOC satellites, which equals \(-\)37 mm is smaller than the offset for Galileo IOV satellites, which equals \(-\)43 mm. Moreover, the offset for Galileo FOC satellites, which were launched into extended highly eccentric orbits (SVN 201 and 202), is smaller than for the other Galileo FOC satellites. The mean offset for GLONASS-K1 equals \(-\)13 \(\pm\) 21 and is smaller than for GLONASS-M satellites, for which the offset is \(-\)18 \(\pm\) 36 mm. The offset for GLONASS-M+ equals 13 \(\pm\) 28 mm and clearly diverges from the other GLONASS satellites. The GLONASS M+ is the only GLONASS satellite with the regular mean positive offset of SLR residuals (see Table 3 and Table 2). The dependency between SLR residuals to multi-GNSS and the local time of observations can also be analyzed in the GOVUS service (see Figure 7). Only some of SLR stations are able to track GNSS satellites in the daylight. The local time of measurements has an impact on the values of residuals and the number of observations collected by SLR stations. The station Graz (7839), operating in the low-energy regime, delivers more observations at night. In contrary, there is no difference in the number of observations performed during the daytime and at night in Yarragadee (7090), however the mean SLR residuals for observations collected at night are nearly twice as large as in the daytime. Figure 6: Histograms of SLR residuals related with particular laser stations; Dataset from August 2015–July 2017, consisted of only SLR residuals related to GLONASS-M satellites with uncoated LRA. Abbreviations used: AVG, average; ST_DEV, standard deviation; No. Obs., number of observations.