Papers & Publications
Out-of-the-box telecommunication systems thanks to our Research and Development Department
The NEFOCAST System for Detection and Estimation of Rainfall Fields by the Opportunistic Use of Broadcast Satellite Signals
EEE Aerospace and Electronic Systems Magazine – June 2019
In this paper, we present results from the NEFOCAST Project, funded by the Tuscany Region, aiming at detecting and estimating rainfall fields from the opportunistic use of the rain-induced excess attenuation incurred in the downlink channel by a commercial DVB satellite signal. The attenuation is estimated by reverse-engineering the effects of the various propagation phenomena affecting the received signal, among which, in first place, the perturbations factors affecting geostationary orbits, such as the gravitational attraction from the moon and the sun and the inhomogeneity in Earth mass distribution and, second, the small-scale irregularities in the atmospheric refractive index, causing rapid fluctuations in signal amplitude. The latter impairments, in particular, even if periodically counteracted by correction maneuvers, may give rise to significant departures of the actual satellite position from the nominal orbit. A further problem to deal with is the daily and seasonal random fluctuation of the rain height and altitude/size of the associated melting layer. All of the above issues lead to nonnegligible random deviations from the dry nominal downlink attenuation, that can be misinterpreted as rain events. In this paper, we show how to counteract these issues by employing two differentially configured Kalman filters designed to track slow and fast changes of the received signal-to-noise ratio, so that the rain events can be reliably detected and the relevant rainfall rate estimated.
Received signal-to-noise ratio, NEFOCAST system, broadcast satellite signals, NEFOCAST Project, rain-induced excess attenuation, downlink channel, commercial DVB satellite signal, propagation phenomena, perturbations factors, geostationary orbits, gravitational attraction
Real-time high resolution rainfall maps from a network of ground-based interactive satellite terminals: the NEFOCAST project
Proc. IoT Vertical and Topical Summit for Agriculture, Monteriggioni, Italy, May 2018.
NEFOCAST project for real-time precipitation estimation from Ku satellite links: Preliminary results of the validation field campaign
Proc. URSI Atlantic Radio Science Meeting, Gran Canaria, Spain, May-June 2018.
NEFOCAST is a project funded by the Tuscany Region Goverment (Italy) that aims at setting up, and demonstrating through field experiments, the concept of a system able to provide precipitation maps in real-time based on the attenuation measurements collected by a dense population of interactive satellite terminals (called SmartLNB, smart Low-Noise Block converter) commercially used as bidirectional modems. The system does not require the set-up of specific precipitation measuring instruments, but uses telecommunication links. An algorithm that converts the SmartLNB raw data into attenuation values, and infers rainfall rate from the total signal attenuation provided by the devices and from the knowledge of the link geometry, has been developed. An experimental campaign will take place in 2018 in Tuscany with the purpose of validating the NEFOCAST estimates, obtained through a dense population of smartLNBs and an X-band dual-polarization weather radar, purposely installed. During a preliminary test phase, performance of the algorithm has been assessed tested by comparing data from individual smartLNBs with tipping bucket rain gauge and a co-located laser disdrometer. This study presents and discusses results obtained during the test phase, focusing on disdrometer evaluation.
rainfall rate, individual smartLNBs, preliminary test phase, X-band dual-polarization weather radar, NEFOCAST estimates, experimental campaign, link geometry, total signal attenuation, SmartLNB raw data, telecommunication links, specific precipitation measuring instruments, validation field campaign, ku satellite links, real-time precipitation estimation