## 3 Testing and Results
### Test-2: Hovering Close to a Tall Wall  
The second test differs from the first one for the obstacle used to obstruct the sky visibility. In this test, the almost-30-meter-high north-east facade of the ITC building (see orange dots in Figure 2) was used. Note that the impact of such an obstacle is increased at the test site's latitude (52 degrees) due to the hole in GNSS constellations above the poles (see the orbital plane details in [31]), which leaves no satellites orbiting at mid-low elevations in the north direction, the one left free from the test obstacle. In this condition, the impact of the satellite geometry on the positioning accuracy is higher. This makes  
Figure 5: Statistics related to est-1. The (**left**) histogram reports the time to lose the ambiguity fixing condition starting from the initial position, while the (**right**) one shows the time required to re-gain the re-fix the solution after having left the obstacle. the test scenario one of the worst possible in the hovering of a drone close to a tall wall simulating the case in which a drone is used in the inspection of a rock quarry wall or a tall concrete dam. In this test, 31 runs were performed, leaving the receiver against the wall for 15 s in the first ten runs, 30 s in the runs 11-20, and 75 s in the last runs, except for the 29 th. The approaching speed of the cart was in the order of 1 m/s. Figure 6 reports the horizontal coordinates surveyed during the test. In these pictures, black, blue, and red are again used to represent the fixed, floating, and single solutions, respectively. The red triangles represent the last fixed solution of each run, while the green ones denote the first ambiguity of fixed solutions on the way back of the cart. Also in this test, the fixing conditions were lost in different positions for the different runs, mainly within 5 m from the obstacle, whereas the re-fix occurred most of the time close to the initial position of the cart. More specifically, the fixing condition was lost 1-2 m far from the wall in the first runs, while later, this position moved back to 5-6 m (see the run numbers in Figure 6). This variability in this position may be due to the changing satellite constellation: by looking at the bottom time series plotted in Figure 7a, which reports the number of GNSS satellites in sight at each measuring epoch, this value varies between 7 and 14 and tends to decrease over time. This probably causes the higher impact of the obstacle on the ambiguity fixing in the late runs. It is worth noting that in test-2, the obstacle is much higher than in test-1, thus causing more of a multipath effect during the approach to it, while on the other hand, it does not constitute a complete occlusion to the sky visibility. Figure 6: Map of the horizontal coordinates surveyed during the test. The black, blue, and red dots are used to represent fixed, floating, and single solutions, respectively. The triangles show the positions of the last fixed solution approaching the building facade or the first fixed solution on the way back to the initial position. The numbers close to the red triangles are related to the test runs. Figure 7a also shows the up component of the fixed solutions only (top) and the estimated vertical precision VRMS (middle time series). As for Figure 3, the vertical component is shown, as it is the best constrained along the cart path. Looking at the zoom-in in Figure 7b, it can be noticed that right before switching to the float condition, the accuracy of the coordinates strongly worsened. Nevertheless, the VRMS parameter appears to be quite representative of the actual positioning quality and thus might be used to highlight possibly unreliable fix solutions. Some false fixed solutions occurred during the test, as highlighted both in Figure 6 and in the top plot of Figure 7a. In such cases, the VRMS coherently increased at the measuring epochs of the outlier solutions.