Multi-resolution compressive sensing inversion of scattering data

Abstract : This paper proposes a novel technique for retrieving the dielectric features of weak scatterers in microwave imaging by means of a Compressive Sensing (CS)-based method enhanced by a multi-zoom strategy. A Relevance Vector Machine (RVM) is used to invert the data of the problem recast in a Bayesian framework, exploiting the combination of the a-priori information on the sparseness of the unknowns and the acquired knowledge during the iterative multi-scaling methodology. Representative results are presented to illustrate advantages and limitations of the proposed method.
Type de document :
Communication dans un congrès
11th European Conference on Antennas and Propagation (EuCAP 2017), Mar 2017, Paris, France. pp.1599-1602, 2017, 〈10.23919/EuCAP.2017.7928548〉
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https://hal.archives-ouvertes.fr/hal-01583449
Contributeur : Andrea Massa <>
Soumis le : jeudi 7 septembre 2017 - 12:09:59
Dernière modification le : jeudi 26 avril 2018 - 17:21:54

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Lorenzo Poli, Giacomo Oliveri, Andrea Massa. Multi-resolution compressive sensing inversion of scattering data. 11th European Conference on Antennas and Propagation (EuCAP 2017), Mar 2017, Paris, France. pp.1599-1602, 2017, 〈10.23919/EuCAP.2017.7928548〉. 〈hal-01583449〉

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