Kalman Tracking of GEO Satellite Signal for Opportunistic Rain Rate Estimation

In the NEFOCAST project we aim at estimating rainfall by the opportunistic use of the signal attenuation due to the propagation channel in satellite communications. The estimation is performed by reverse engineering the effects of the various propagation phenomena on the satellite signal. However, the accuracy of the estimation is affected by several factors: in first place the rapid fluctuations in signal amplitude caused by small-scale irregularities in the tropospheric refractive index; secondly, the perturbations of the orbit of GEO satellites, such as the gravitational effects of the moon and the sun, which, even if periodically counteracted by correction maneuvers, nevertheless cause residual orbit inclinations. The problem with all these factors is that they can cause large deviations in the clear-sky measurements that can be misinterpreted as rain events. In this paper we address these problems by employing two Kalman filters designed to track slow and fast changes of the received signal energy, so that the rain events can be reliably estimated.