## 5 Signal Processing and Results of an In-Field Test
### Signal Processing Principles  
With the scope of implementing the reflectometry functionalities, a MATLAB(r)-based software receiver has been modified here to make it able to properly process the data from the four channels of the sensor. The principle of this architecture comes from the GPS software receiver described in [38], and it has been chosen for the many advantages that the software-defined paradigm includes, in particular for its flexibility. Particular attention was paid to the study of the algorithms to detect the reflected signal to cope with the major challenges presented by the reflected signals, namely the extremely low power and the very short phase coherence.  
In fact, the reflected signal is not a single specular reflection from the so-called specular point, but it is the sum of several contributions (scattering) from a reflecting area, namely the glistening zone, whose size depends on the incidence angle, the receiver altitude and the surface roughness (models exist that allow one to find a suitable approximation).  
This scattering effect causes a much shorter phase coherence compared to the direct signal, in particular in dynamic environments, such as in flight; for this reason, an open-loop strategy is in general advisable to detect the reflections.  
Furthermore, the scattering effect, reducing the reflected power reaching the nadir-pointing antenna, worsens for lower incident angles, in particular for the LHCP components. Thus, although Equation (5) takes the incidence angle into account, the accuracy of the estimate decreases when the satellite elevation reduces [34]: the SNR diminishes, meaning that the impact of the noise becomes heavier on the measurement. For this reason, the surface scattering effect needs to be mitigated in order to estimate the actual reflected signal power; this can be done by averaging over time the measurements.  
Furthermore, in order to detect a low-power signal, the integration time needs to be increased as much as possible, even if this means getting lower spatial resolution on the measurements. However, the coherent integration time cannot be longer than the signal coherence interval; therefore, a trade-off solution needs to be found. A key strategy introduced in the software scheme is the channel aiding, which means that information from the direct signal processing is exploited to detect the reflected signal, since the Doppler frequency of the two signals is expected to differ by only a few tenths of Hertz, and the delay is expected to be within an interval depending on the satellite elevation and the aircraft altitude.  
The effects of the secondary multipath are neglected here. Concerning the reflected signal, the interest is on the principal reflection; it might occur that some unexpected (and undesired) reflections from some targets, including buildings, are received together with the reflection from the considered reflection point on the terrain, as a multipath signal. Such cases are not predictable, but they are expected to be rare, and such an error is considered acceptable for this kind of application. Concerning the direct signal, undesired multipath signals may occur due to the reflections from the aircraft or the UAV. However, given the small dimensions of the aircraft on which the sensor is designed to be mounted and given the position of the antenna on the wing, the multipath effects are expected not to be significant with respect to the noise [23]. Anyway, a better analysis of the antenna gain together with the multipath effects should be included in the future developments of the sensor.