## 5 Conclusions  
In this study, a big computational effort was produced to analyze 1 Hz multi-constellation kinematic data acquired during a one-hour field survey, planned to maximize Galileo satellites availability. The acquired data included a contemporary acquisition through an MMS equipped with a POS/LV produced by the Applanix corporation. The MMS acquisition was used as a reference trajectory, and the robustness of its solution was the most important hypothesis for the results shown in this study. This hypothesis can be considered always valid for research since it was found by coupling the GNSS technology with precise inertial instruments. Moreover, the MMS solution was calculated considering a higher amount of GNSS satellites when compared with the number of satellites used to perform the tests (four, five, and six). Lastly, only the L1, G1, and E1 frequencies were used in this experiment. In order to present a real kinematic comparison between Galileo, GPS, and GLONASS satellite positioning systems, a reduced operational status was simulated for GPS and GLONASS. Moreover, it was possible to implement post-processed differential solutions with the Open-Source Software RTKLIB, thanks to the GNSS acquisitions of reference stations close to the surveyed areas. The performed comparisons, whenever possible, were analyzed also by means of a statistical test. The outputs showed a clear and statistically significant planimetric performance of the Galileo positioning system, whereas the same result was not obtained from an altimetric point of view. However, in the authors' opinion, this was especially due to the very small number of Galileo satellites and to their geometrical configurations. Although these results were obtained with several computations, especially for the Galileo altimetric performance, they need to be reinforced by further experimental evidence. For this reason, they should be considered as preliminary results achieved by using a reference trajectory. Moreover, it is possible to conclude that the novel system is very promising also when used alone; in a disadvantaged comparison, it was able to produce better planimetric accuracy than the GPS and GLONASS positioning systems in a kinematic survey. Future development of this work can include the kinematic inter-constellation comparison, the evaluation of the robustness of velocity and acceleration estimation with the Galileo constellation, and attitude estimations. The following are available online at [[http://www.mdpi.com/2220-9964/7/3/122/s1](http://www.mdpi.com/2220-9964/7/3/122/s1)]([http://www.mdpi.com/2220-9964/7/3/122/s1](http://www.mdpi.com/2220-9964/7/3/122/s1)). For a description of the following figures, please see the Appendix A section. Figure S1: \(\Delta_{\text{D,1 gal\_vs\_gps}}\), Figure S2: \(\Delta_{\text{D,1 gal\_vs\_gps}}\), Figure S3: \(\Delta_{\text{D,1 gal\_vs\_gps}}\), Figure S4: \(\Delta_{\text{D,1 gal\_vs\_glo}}\), Figure S5: \(\Delta_{\text{D,2 gal\_vs\_glo}}\), Figure S6: \(\Delta_{\text{D,2 gal\_vs\_glo}}\), Figure S7: \(\Delta_{\text{D,2 gal\_vs\_gps}}\), Figure S8: \(\Delta_{\text{D,2 gal\_vs\_glo}}\), Figure S9: \(\Delta_{\text{D,2 gal\_vs\_gps}}\), Figure S10: \(\Delta_{\text{D,2 gal\_vs\_glo}}\), Figure S11: \(\Delta_{\text{H,1 gal\_vs\_gps}}\), Figure S12: \(\Delta_{\text{H,1 gal\_vs\_gps}}\), Figure S13: \(\Delta_{\text{H,1 gal\_vs\_gps}}\), Figure S14: \(\Delta_{\text{H,1 gal\_vs\_glo}}\), Figure S15: \(\Delta_{\text{H,2 gal\_vs\_gps}}\), Figure S16: \(\Delta_{\text{H,2 gal\_vs\_gps}}\), Figure S17: \(\Delta_{\text{H,2 gal\_vs\_gps}}\), Figure S18: \(\Delta_{\text{H,2 gal\_vs\_glo}}\), Figure S19: \(\Delta_{\text{H,2 gal\_vs\_gps}}\), Figure S20: \(\Delta_{\text{H,2 gal\_vs\_glo}}\). The authors thank Leica for their technical support and for giving access to SmarNet ItalPos Galileo data used for the processing and analyses presented in this paper. All the authors equally contributed to the experimental design (including the field survey) and manuscript revision of this work.