## 5 Signal Processing and Results of an In-Field Test
### Test Campaign Results
However, the level of accuracy reached is as expected from the project requirements, given the low-cost devices, which cause several residual errors, not including accurate hardware calibration of the antennas (using inertial systems) and not calibrating other effects, such as the system vibrations. Figure 12: Reflection coefficient: comparison between expected and measured values, for different reflecting surfaces and satellite elevations. A further test was done by comparing the retrieved values of soil moisture, for the same area, computed using the reflections from different satellites. This test can be a good proof of the goodness of the system, allowing a comparison between different measurements (signals from different satellites) of the same quantities (same area). This was possible thanks to the multiple passing of the aircraft close to the same area during the flight test. In this way, it happens that different reflections, corresponding to different satellites and then to different incidence angles and to different reflection coefficients, must theoretically give the same result in terms of dielectric constant and moisture, since the reflection points lay in the same area. Applying the soil moisture retrieval algorithm as explained in Section 4.1 to the real in-flight measurements, it is found that when the reflection point is on the lakes' surface, the average estimated value of the so-called volumetric soil moisture, _i.e._, the estimate of the soil water content, is as expected \(m_{v}\simeq 1\) for all of the PRNs, 13, 15 and 30. Over other regions, for instance cultivated fields, when the reflection points of different satellites lay on the same field (visible from the map, with the satellite view), the mean value of the estimated soil parameters match for different satellites. In the Mareschi humid zone, for instance, the measured mean value is \(m_{v}=0.75\) for PRN 13, while it is \(m_{v}=0.78\) for PRN 15. The matching between these measurements, together with the comparison between the expected and the obtained measured reflection coefficients in Figure 12, represents a good test of the measurement system, when _in situ_ measurements with other sensors are not available. As said before, the results described above are obtained from the processing of the LHCP reflection. Although it is expected that the processing of the RHCP measurement can improve the accuracy of the overall results, as discussed in Section 4.2, an insufficient cross-polarization separation at the antenna stage is likely responsible for the little improvement observed in our data collections. For this reason, we limit the present discussion to the results of the LHCP-only approach mentioned in Section 4.1. Nonetheless, this test proved the prototype to be effective in order to provide GPS reflection measurements useful to retrieve soil parameters, such as its moisture. The overall accuracy of the methodology depends on several parameters, including the antenna performance, particularly in terms of cross-polarization separation, the applicability of the model used to estimate the soil parameters and the accuracy of the knowledge of the terrain composition.