An innovative method for the inversion of ground penetrating radar (GPR) measurements is presented. The proposed inverse scattering (IS) approach is based on the exploitation of wide-band data according to a multi-frequency (MF) strategy, and integrates a customized particle swarm optimizer (PSO) within the iterative multi-scaling approach (IMSA) to counteract the high non-linearity of the optimized cost function. If from the one hand the IMSA provides a reduction of the ratio between problem unknowns and informative data, on the other hand the stochastic nature of the PSO solver allows to "escape" from the high density of false solutions of the MF-IS subsurface problem. A set of representative numerical results verifies the effectiveness of the developed approach, as well as its superiority with respect to a deterministic implementation.
A computational method for the inversion of wide-band GPR measurements / Salucci, M.; Tenuti, L.; Poli, L.; Oliveri, G.; Massa, A.. - STAMPA. - (2016), pp. 1-6. (Intervento presentato al convegno 6th International Workshop on New Computational Methods for Inverse Problems, NCMIP 2016 tenutosi a Cachan, France nel 20 May 2016).
A computational method for the inversion of wide-band GPR measurements
Salucci, M.;Tenuti, L.;Poli, L.;Oliveri, G.;Massa, A.
2016-01-01
Abstract
An innovative method for the inversion of ground penetrating radar (GPR) measurements is presented. The proposed inverse scattering (IS) approach is based on the exploitation of wide-band data according to a multi-frequency (MF) strategy, and integrates a customized particle swarm optimizer (PSO) within the iterative multi-scaling approach (IMSA) to counteract the high non-linearity of the optimized cost function. If from the one hand the IMSA provides a reduction of the ratio between problem unknowns and informative data, on the other hand the stochastic nature of the PSO solver allows to "escape" from the high density of false solutions of the MF-IS subsurface problem. A set of representative numerical results verifies the effectiveness of the developed approach, as well as its superiority with respect to a deterministic implementation.File | Dimensione | Formato | |
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NCMIP-2016.Inverse-GPR-PSO.pdf
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