Intensity estimation after detection for accumulated rainfall estimation

This work focuses on optimizing the estimation of accumulated rain from measurements of the attenuation level of signals from commercial microwave links (CMLs). The process of accumulated rain estimation is usually based on estimation after detection, where it is first determined whether there is rain for a specific period, and then the accumulated rain at the detected rainy period is estimated. Naturally, errors in detection affect the accuracy of the consequent accumulated rain estimation. Traditionally, the detection and the estimation steps are designed independently. The detection threshold is arbitrarily set at the lowest level that would be declared as rain, without considering its effect on the accuracy of the accumulated rain estimation. This study applies a novel method that sets a detection threshold to optimize estimation after detection and apply it for accumulated rain estimation. It is based on optimizing a post-detection estimation risk function that incorporates both the estimation and detection-related errors; this essentially takes into consideration the coupling of the detection and the estimation stages and thus optimizes the overall accumulated rainfall estimation. The proposed approach is applied to actual CML attenuation measurements taken from a cellular network in Gothenburg, Sweden. This demonstrates that the proposed method achieves better accuracy for accumulated rain estimation compared with the detection threshold being set independently.