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Open AccessArticle

Qualitative Methods for the Inverse Obstacle Problem: A Comparison on Experimental Data

by Martina T. Bevacqua 1,2,*,† and Roberta Palmeri 1,†
1
DIIES, Department of Information Engineering, Infrastructures and Sustainable Energy, Università Mediterranea di Reggio Calabria, via Graziella, Loc. Feo di Vito, 89124 Reggio Calabria, Italy
2
CNR-IREA, National Research Council of Italy, Institute of Electromagnetic Sensing of the Environment, via Diocleziano 328, 80124 Napoli, Italy
*
Author to whom correspondence should be addressed.
The paper is a result of a joint contribution of both the authors, from conceptualization to final writing and editing.
J. Imaging 2019, 5(4), 47; https://doi.org/10.3390/jimaging5040047
Received: 7 March 2019 / Revised: 29 March 2019 / Accepted: 8 April 2019 / Published: 10 April 2019
(This article belongs to the Special Issue Microwave Imaging and Electromagnetic Inverse Scattering Problems)
Qualitative methods are widely used for the solution of inverse obstacle problems. They allow one to retrieve the morphological properties of the unknown targets from the scattered field by avoiding dealing with the problem in its full non-linearity and considering a simplified mathematical model with a lower computational burden. Very many qualitative approaches have been proposed in the literature. In this paper, a comparison is performed in terms of performance amongst three different qualitative methods, i.e., the linear sampling method, the orthogonality sampling method, and a recently introduced method based on joint sparsity and equivalence principles. In particular, the analysis is focused on the inversion of experimental data and considers a wide range of (distinct) working frequencies and different kinds of scattering experiments. View Full-Text
Keywords: inverse obstacles problem; inverse source problem; joint sparsity; linear sampling method; microwave imaging; orthogonality sampling method inverse obstacles problem; inverse source problem; joint sparsity; linear sampling method; microwave imaging; orthogonality sampling method
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Bevacqua, M.T.; Palmeri, R. Qualitative Methods for the Inverse Obstacle Problem: A Comparison on Experimental Data. J. Imaging 2019, 5, 47.

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