How can Signal Processing Enhance Opportunistic Precipitation Sensing?
Jonatan Ostrometzky1, Hagit Messer1
1 School of Electrical and Computer Engineering, Tel Aviv University, Israel
Signal processing can be described as the analysis and interpretation of signals to extract useful information. In this keynote, we will elaborate on three specific questions related to the use of commercial microwave links (CMLs) for opportunistic rain monitoring. The first question is: how much performance is lost in rain-field reconstruction when modeling a CML as a single virtual rain gauge located at its center, thereby disregarding the fact that it collects information along a line? Second, we present an analysis of how much rain-intensity information can be extracted from CMLs’ min-max attenuation measurements, compared to instantaneous samples at different sampling rates. Third, we will show the relation between CMLs-network density and the achievable resolution of rainfall maps.
Presentation slides:
