## 3 Results
### Comparisons Results
show the number of epochs in which it was possible to execute the simple comparisons between the means and the number of times, expressed in percentage, in which Galileo performed better. The \(t\)-test summary columns show the number of epochs with one sample \(t\)-test, the average \(p\)-value, the number of epochs, expressed in percentage, in which the \(p\)-value was less than 0.5.  
and \(\Delta_{\rm H2}\) and is a direct consequence of the increasing number of satellites associated with a higher rate of fixed ambiguities. The statistical assessment data of the \(\Delta_{\rm D1}\) and \(\Delta_{\rm D2}\) results in Table 4 provide a summary of the outcomes. In this case, the aim was to test if the found differences were statistically significant and which percentage of these differences could be considered at the 5% significance level. The lower the \(p\)-value, the stronger the statistical significance of the differences will be. No statistical tests were performed over the \"gal_vs_glo_4\" groups, since the imposed conditions to perform the tests were not satisfied (see point f) Section 2.3.3). As expected, because of the higher number of available combinations, more tests were performed with the GPS system. With regard to \(\Delta_{\rm D1}\) and \(\Delta_{\rm D2}\) comparisons, Table 4 depicts a common scenario both for the fixed and the float solutions. The found differences became more significant when the number of satellites rose. They reached the maximum statistical significance in the \"\(\Delta_{\rm D,1}\) gal_vs_gps_6\" comparison. An empirical evidence of the better Galileo performance characterized by planimetric solutions closer to the MMS trajectory, when comparing the previous columns with these data, is evident for this real case study. Also Figure 11 (see Appendix A) reveals that, when the GPS system performed better, the found differences were not significant (the green point depicts quite elevated \(p\)-values). With regards to the \"\(\Delta_{\rm D,1}\) gal_vs_glo_6\" group, despite the superiority of the Galileo system (Figure 11b), the lower degree of statistical significance (if compared to the \"\(\Delta_{\rm D,1}\) gal_vs_gps_6\") could also be due to the lower number of GLONASS combinations. From the altimetric point of view (able 4: rows 13 to 24), the proposed scenario shows a better performance of GPS and GLONASS systems. However, the \"gal score\", in this case, empirically indicates that this evidence is not as strong as in the case of the planimetric analysis. Table 4 also demonstrates a positive trend for the \"gal score\" coupled with the increasing number of satellites. As far as the statistical assessment of the altimetric comparison is concerned, a lower rate of statistical significance depicted both by average \(p\)-value and by the number of tested epochs with a \(p\)-value \(<0.05\) could be seen. This is clearly shown in Figure 11c,d (see Appendix A), in which the lower degree of statistical significance is particularly marked for the \"\(\Delta_{\rm H,1}\) gal_vs_glo_6\" (Figure 11d--the green points related to the \(p\)-values). This empirical evidence, encountered especially in the altimetric comparisons, can be explained by the lower altimetric accuracy of the analyzed solutions. Therefore, The lower Galileo altimetric accuracy may be related to a nonoptimal vertical configuration of the satellites available for the kinematic surveys. Lastly, the figures listed in Table 4 and provided as Supplementary Material feature a detailed visual output of the performed tests. The description useful for their interpretation can be found in the Appendix A section.