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arXiv · 2108.01627

Multi-Frequency GPR Microwave Imaging of Sparse Targets Through a Multi-Task Bayesian Compressive Sensing Approach

Marco Salucci·Nicola Anselmi
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Abstract

An innovative inverse scattering (IS) method is proposed for the quantitative imaging of pixel-sparse scatterers buried within a lossy half-space. On the one hand, such an approach leverages on the wide-band nature of ground penetrating radar (GPR) data by jointly processing the multi-frequency (MF) spectral components of the collected radargrams. On the other hand, it enforces sparsity priors on the problem unknowns to yield regularized solutions of the fully non-linear scattering equations. Towards this end, a multi-task Bayesian Compressive Sensing (MT-BCS) methodology is adopted and suitably customized to take full advantage of the available frequency diversity and of the a-priori information on the class of imaged targets. Representative results are reported to assess the proposed MF-MT-BCS strategy also in comparison with competitive state-of-the-art alternatives.

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Marco Salucci, Nicola Anselmi. 2021-08-03. Multi-Frequency GPR Microwave Imaging of Sparse Targets Through a Multi-Task Bayesian Compressive Sensing Approach. https://arxiv.org/abs/2108.01627

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