Abstract
The use of special-purpose wireless microwave links (MLs) in order to monitor rainfall is well understood. However, the use of existing MLs, which are part of the cellular communication networks backhaul, presents new signal processing challenges. Together with the exciting monitoring opportunities that lie in the large number and ubiquitousness of such MLs, the opportunistic use of the measurements is determined by the protocols used by the cellular providers, whose purpose is reliable communication rather than environmental monitoring. To minimize the bandwidth and storage resources, typical commercial transmission protocols log the Received Signal Level (RSL) measurements of a microwave signal at 15 minute intervals, where only the maximum and the minimum values of the RSL for every 15 minute period are logged. While past studies dealt with this non-linear pre-processing of the RSL measurements in an ad-hoc manner, we present a systematic approach for estimating the accumulated rainfall during moderate-to-heavy storms from the actual RSL measurements, that is - from the sequence of the minimal values of the RSL (which correspond to the maximal attenuation levels) in 15 minute intervals. Using the extreme value theory we find an approximated Maximum Likelihood estimate of the accumulated rainfall. We apply the suggested technique to actual data and we show that it provides more accurate results than the alternatives.
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