2021/08/03 by Marco Salucci, Nicola Anselmi, Salucci, Marco +1
Engineering · #FOS: Computer and information sciences #Geophysical Methods and Applications #Information Theory (cs.IT) #Microwave Imaging and Scattering Analysis #Sparse and Compressive Sensing Techniques
paper · pdf · doi:10.48550/arxiv.2108.01627
openalex publication_date 2021/08/03 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
An innovative inverse scattering (IS) method is proposed for the quantitative\nimaging of pixel-sparse scatterers buried within a lossy half-space. On the one\nhand, such an approach leverages on the wide-band nature of ground penetrating\nradar (GPR) data by jointly processing the multi-frequency (MF) spectral\ncomponents of the collected radargrams. On the other hand, it enforces sparsity\npriors on the problem unknowns to yield regularized solutions of the fully\nnon-linear scattering equations. Towards this end, a multi-task Bayesian\nCompressive Sensing (MT-BCS) methodology is adopted and suitably customized to\ntake full advantage of the available frequency diversity and of the a-priori\ninformation on the class of imaged targets. Representative results are reported\nto assess the proposed MF-MT-BCS strategy also in comparison with competitive\nstate-of-the-art alternatives.\n