F. Giannetti, M. Moretti, R. Reggiannini, A. Petrolino, G. Bacci, E. Adirosi, L. Baldini, L. Facheris, S. Melani, A. Ortolani
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The Potential of Smartlnb Networks for Rainfall Estimation
NEFOCAST is a research project that aims at retrieving rainfall fields from channel attenuation measurements on satellite links. Rainfall estimation algorithms rely on the deviation of the measured Es/N0 from the clear-sky conditions. Unfortunately, clear-sky measurements exhibit signal fluctuations (due to a variety of causes) which could generate false rain detections and reduce estimation accuracy. In this paper we first review the main causes of random amplitude fluctuations in the received Es/N0, and then we present an adaptive tracking algorithm based on two Kalman filters: one that tracks slow changes in Es/N0 due to external causes and another which tracks fast Es/N0 variations due to rain. A comparison of the outputs of the two filters confirms the reliability of the rainfall rate estimate.
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