In recent years, several emerging technologies in modern radar system design are attracting the attention of radar researchers and practitioners alike, noteworthy among which are multiple-input multiple-output (MIMO), ultra wideband (UWB) and joint communication-radar technologies. This thesis, in particular focuses upon a cognitive approach to design these modern radars. In the existing litera...

Imaging the interior of a region with waveforms recorded on the surface is a key application of scattering theory in geophysics, medical imaging and many other fields. In this chapter I will discuss how the waveform inversion problem can be formulated in terms of statistical inference. Statistical methods are essential in order to be able to take into account the limited, uncertain nature of th...

Abstract This brief summarizes some of the main results I obtained during my Ph.D. studies at Politecnico di Milano, under supervision Professor Stefano Tubaro. The thesis provides contributions to understanding advantages, and limitations, data-driven deep learning approaches geophysical inverse problems, with a special focus on Convolutional Neural Networks (CNNs). Exploration Geophysics aims...

a r t i c l e i n f o We describe the state of the art of scientific research on the earthquake cycle based on the analysis of Synthetic Aperture Radar (SAR) data acquired from satellite platforms. We examine the achievements and the main limitations of present SAR systems for the measurement and analysis of crustal deformation, and envision the foreseeable advances that the Sentinel-1 data wil...