## 5 Conclusions  
This technical note aims to provide readers with insights about the performances of a GNSS/RTK module when used to locate with centimeter-level precision a drone flying in critical environments, with a reduced or no GNSS signal. In particular, we tested a module based on the Ubox F9P receiver, mounted on a cart so that it was possible to move it in critical positions where GNSS signals are denied. The coordinates and ancillary parameters recorded in the QGround Control log files were analyzed to better understand the behavior of the receiver. Three main tests were conceived to simulate practical scenarios of a drone flying close to, or under, human-made objects that partially or completely obstruct the sky, thus denying satellite signals.  
The performed tests give drone users some practical and relevant insights into the quality of the GNSS positioning in these conditions. Only fixed solutions can deliver accurate values of the drone's position. HRMS/VRMS parameters have been shown to be good proxies to determine wrong or low-quality positions and should be accurately considered in flying from outdoor to indoor conditions. Another important achievement of our tests is that the hovering flight of the drone does not help the re-fixing of the phase ambiguities, making the solution more prone to wrong localizations.  
The tests were performed using the master station within a hundred meters, as is the case in most real cases with drones. In this regard, the use of double-frequency receivers gives similar behaviors in terms of fixing time for larger distances, too. Nevertheless, depending on the hardware used, the radio link between the master and the rover might become the limiting factor to the RTK positioning quality. To provide drones users with more comprehensive results, different baseline setups, and a broader set of locations, simulated obstacles and GNSS antennas could be analyzed.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Necessity** & **Possible Solution** \\ \hline Navigate the drone with a precise positioning (coherence of the coordinates within 10 cm). & Use only RTK solutions marked as “fix”, not considering those acquired under “float” or “single” conditions. \\ Avoid trusting “fix” solution possibly affected by significant errors (\textgreater{}10\) cm, up to meters). & Set a threshold on the HRMS/VRMS parameters (3 to 5 cm), and reject exceeding solutions. \\ Avoid “false fix” potentially occurring after re-fixing the solution out of a GNSS-denied environment. & Keep the drone moving right after re-fixing the phase ambiguities (1 m or more in plan, or 0.5 m vertically) before approaching the obstacle again instead of slowly hovering close to it. \\ \hline \hline \end{tabular}
\end{table}
Table 1: Good practices to be implemented in a drone flight under potentially critical conditions for the GNSS navigation system.  
The experiments performed in this case study were limited to the assessment of the positioning quality, considering the few parameters normally available in QGround Control and other drone software solutions. This was carried out to keep the results close to the practical experience of experts assembling and delivering drone solutions. However, more precise reference solutions (for the cart trajectories), as well as a more thorough analysis of parameters such as DOP, constellation sky-plots, and multi-path influence, would have probably improved the presented analysis, despite not adding further practical insights to the results of this work.  
Methodology, L.T. and F.N.; data acquisition, L.T. and F.N.; data analysis, L.T.; resources, S.G.; writing--original draft preparation, L.T.; writing--review and editing, L.T., F.N. and S.G.; visualization, L.T. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Data Availability Statement: Data are contained within the article.  
The authors declare no conflicts of interest.