Remote sensing and electromagnetic modeling applied to weather and forward scatter radar

This dissertation deals with electromagnetic modelling and data analysis, related to radar remote sensing and applied to forward scatter and meteorological polarimetric systems. After an overview of radar fundamentals to introduce the general terminology and concepts, results are presented at the end of each chapter. In this respect, a generalized electromagnetic model is first presented in order to predict the response of forward scatter radars (FSRs) for airtarget surveillance applications in both near-field and far-field regions. The model is discussed for increasing levels of complexity: a simplified near-field model, a near-field receiver model and a near-field receiver and transmitter model. FSR results have been evaluated in terms of the effects of different target electrical sizes and detection distances on the received signal, as well as the impact of the trajectory of the moving objects and compared with a customized implementation of a full-wave numerical tool. Secondly, a new data processing methodology, based on the statistical analysis of ground-clutter echoes and aimed at investigating the monitoring of the weather radar relative calibration, is presented. A preliminary study for an improvement of the ground-clutter calibration technique is formulated using as a permanent scatter analysis (PSA) and applied to real radar scenarios. The weather radar relative calibration has been applied to a dataset collected by a C-band weather radar in southern Italy and an evaluation with statistical score indexes has drawn through the comparison with a deterministic clutter map. The PSA technique has been proposed using a big metallic roof with a periodic mesh grid structure and having a hemispherical shape in the near-field of a polarimetric C-band radar and evaluated also with an ad-hoc numerical implementation of a full-wave solution. Finally, a radar-based snowfall intensity retrieval is investigated at centimeter and millimeter wavelengths (i.e., at X, Ka and W band) using a high-quality database of collocated ground-based precipitation measurements and radar multi-frequency observations. Coefficients for the multifrequency radar snowfall intensity retrieval are empirically derived using multivariate regression techniques and their interpretation is carried out by particle scattering simulations with soft-ice spheroids. For each topic, conclusions are proposed to highlight the goals of the whole work and pave the way for future studies.