Exploiting sparsity and field conditioning in subsurface microwave imaging of nonweak buried targets. Issue 4 (15th April 2016)

• Record Type: Journal Article
• Authors: Bevacqua, Martina; Crocco, Lorenzo; Donato, Loreto Di; Isernia, Tommaso; Palmeri, Roberta
• Is Part Of: Radio science. Volume 51:Issue 4(2016:Apr.)
• Page Start: 301
• Page End: 310
• Publication Date: 2016-04-15
• Subjects: compressive sensing -- Born approximation -- linear sampling method -- virtual experiments -- fictitious measurements -- point source field approximation; Radio meteorology -- Periodicals; Radio wave propagation -- Periodicals; 621.38405
• DOI: 10.1002/2015RS005904
• Languages: English
• ISSNs: 0048-6604

Abstract

Abstract: An efficient inverse scattering strategy is proposed to achieve dielectric characterization of buried objects in lossy soils. The approach takes advantage of Virtual Experiments and Compressive Sensing to obtain quantitative reconstructions of nonweak targets which are nonsparse in the pixel representation basis, commonly adopted in microwave imaging. In addition, an original strategy is adopted to overcome the relevant information lack arising when data are gathered under aspect‐limited configurations, such as in ground penetrating radar (GPR) surveys. The proposed strategy significantly outperforms the results achievable with the "state of the art" standard approaches since it allows to achieve nearly optimal reconstructions within a linear framework and without increasing the overall computational burden. Numerical examples with simulated data are given to show the feasibility of the proposed strategy. Key Points: In subsurface microwave imaging Born approximation is suitable only for weak scatterers Compressive Sensing provides a powerful tool to achieve nearly optimal reconstructions and superresolution "Virtual Experiments" allow to achieve quantitative reconstructions of nonweak scatterers for aspect‐limited data