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FDEMtools: a MATLAB package for FDEM data inversion

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Abstract

Electromagnetic induction surveys are among the most popular techniques for non-destructive investigation of soil properties, in order to detect the presence of both ground inhomogeneities and particular substances. This paper introduces a MATLAB package, called FDEMtools, for the inversion of frequency domain electromagnetic data collected by a ground conductivity meter, which includes a graphical user interface to interactively modify the parameters of the computation and visualize the results. Based on a non-linear forward model used to describe the interaction between an electromagnetic field and the soil, the software reconstructs the distribution of either the electrical conductivity or the magnetic permeability with respect to depth, by a regularized damped Gauss–Newton method. The regularization part of the algorithm is based on a low-rank approximation of the Jacobian of the non-linear model. The package allows the user to experiment with synthetic and experimental data sets, and different regularization strategies, in order to compare them and draw conclusions.

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Funding

Research partially supported by the Fondazione di Sardegna 2017 research project “Algorithms for Approximation with Applications [Acube],” the INdAM-GNCS research project “Metodi numerici per problemi mal posti,” the INdAM-GNCS research project “Discretizzazione di misure, approssimazione di operatori integrali ed applicazioni,” and the Regione Autonoma della Sardegna research project “Algorithms and Models for Imaging Science [AMIS]” (RASSR57257, intervento finanziato con risorse FSC 2014-2020 - Patto per lo Sviluppo della Regione Sardegna). CF gratefully acknowledges Regione Autonoma della Sardegna for the financial support provided under the Operational Programme P.O.R. Sardegna F.S.E. (European Social Fund 2014-2020 - Axis III Education and Formation, Objective 10.5, Line of Activity 10.5.12).

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Deidda, G.P., Díaz de Alba, P., Fenu, C. et al. FDEMtools: a MATLAB package for FDEM data inversion. Numer Algor 84, 1313–1327 (2020). https://doi.org/10.1007/s11075-019-00843-2

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  • DOI: https://doi.org/10.1007/s11075-019-00843-2

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