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/N0from 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/N0due to external causes and another which tracks fast Es/N0variations due to rain. A comparison of the outputs of the two filters confirms the reliability of the rainfall rate estimate.
The Potential of Smartlnb Networks for Rainfall Estimation
E Adirosi;L Baldini;S Melani;A Ortolani
2018
Abstract
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/N0from 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/N0due to external causes and another which tracks fast Es/N0variations due to rain. A comparison of the outputs of the two filters confirms the reliability of the rainfall rate estimate.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
