## 4 Results and Discussion
### Entire Trajectory: Static and Kinematic Sessions
From GPS, 62% of all the available solutions were those where the deviations of the calculated distances from the (measured) reference distances were less than 1 m, and they were 57% and 48% where the deviations were less than 30 cm and 10 cm, respectively. The results are slightly better for the GNSS solutions. From the overall trajectory statistics, it can be seen that the Xiaomi Mi8 allowed more usable solutions than the u-blox receivers; however, in 99% of cases, the ambiguities were detected as floats. For the phone, 44% of the possible GPS solutions were those where the deviation of the distances from the reference positions was less than 1 m, while 18% and 1% of the total positions on the trajectory were those where the deviations were less than 30 cm and 10 cm, respectively. For the GNSS solutions, only 14% and 5% of the GNSS solutions were those where the deviations of the distances were less than 30 cm and 10 cm, respectively. The results from the u-bloxes are interesting, wherein ZED-F9R seemed to perform better than ZED-F9P both in the number of fixed solutions and in the quality of positioning. Results with Deviation in Distances and Heights below 30 cm  
The statistics for the filtered deviation of distances (Tables 5 and 6) that were less than 30 cm show that the Sepentrio AsteRx-U receiver performed better than others in the number of available solutions (47.5% for the GPS and 57.1% for the GNSS), with deviations in distances calculated with a mean of \(-\)5.8 cm \(\pm\) 6.5 cm for the GPS solutions (Table 5) and \(-\)6.0 cm \(\pm\) 8.4 cm for the GNSS solutions (Table 6). One of the possible reasons for the larger standard deviations in the GNSS solutions could be the fact that Applanix worked in GPS/INS mode; therefore, the results from the GPS are more appropriate for comparisons. Nevertheless, it is noticeable that despite the percentage of GNSS being higher (81.0%) in terms of the GPS-only solutions (70.5%), the number of solutions calculated with fixed ambiguities is correspondingly lower (2176 compared to 2320), which is probably due to the possible insufficient performance of one of the systems used in the multi-constellation solution. drastically. Since there is no overlap between the boxes in any of the Figure 9 plots, it can be concluded that there is a clear difference between the data sets from different receivers. An \(F\)-test was used to detect differences in the variances for the GPS and GNSS solutions. The results are shown in Table 7.  
For the comparison of the variances between the two groups for each of the receivers separately, i.e., the first group represents the GPS solutions and the second represents the GNSS solutions, in both cases, the null hypothesis H\({}_{0}\) that means and variances are equal cannot be rejected. However, the number of possible solutions from the GPS processing in terms of the GNSS is much lower (see Tables 5 and 6). \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Type of GNSS Device**} \\ \hline
**Parameters** & **Septentrio** & **u-blox** & **u-blox** & **Smartphone** \\  & **AsteRx-U** & **ZED-F9P** & **ZED-F9R** & **Xiaomi Mi8** \\ \hline GNSS solutions & 2940 (57.1\%) & 1798 (34.9\%) & 1963 (38.1\%) & 719 (14.0\%) \\ \hline \(\overline{dev}_{-}d_{2D}\) (m) & \(-\)0.060 & \(-\)0.100 & 0.047 & 0.159 \\ s (m) & 0.084 & 0.095 & 0.101 & 0.181 \\ RMSE (m) & 0.100 & 0.138 & 0.111 & 0.204 \\ \hline \(\overline{dev}_{-}d_{3D}\) (m) & \(-\)0.025 & \(-\)0.112 & 0.066 & 0.229 \\ s (m) & 0.098 & 0.140 & 0.083 & 0.034 \\ RMSE (m) & 0.101 & 0.179 & 0.106 & 0.231 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Statistics (mean, standard deviation, and RMSE) for GNSS solutions for filtered values of deviation in distances that were below 30 cm. Situation: entire trajectory (static and kinematic: 5148 total epochs).