Multifrequency Bayesian compressive sensing methods for microwave imaging

Lorenzo Poli 1 Giacomo Oliveri 1 Ping-Ping Ding 2 Toshifumi Moriyama 3 Andrea Massa 1
1 ELEDIA Research Group - Department of Information Engineering and Computer Science
2 L2S - Laboratoire des signaux et systèmes
3 Department of Electrical and Electronic Engineering
Abstract : The Bayesian retrieval of sparse scatterers under multifrequency transverse magnetic illuminations is addressed. Two innovative imaging strategies are formulated to process the spectral content of microwave scattering data according to either a frequency-hopping multistep scheme or a multifrequency one-shot scheme. To solve the associated inverse problems, customized implementations of single-task and multitask Bayesian compressive sensing are introduced. A set of representative numerical results is discussed to assess the effectiveness and the robustness against the noise of the proposed techniques also in comparison with some state-of-the-art deterministic strategies.
Keywords : sparse scatterers imaging Microwave scattering Bayesian Compressive Sensing single-task multi-task
Type de document :
Article dans une revue
Journal of the Optical Society of America, Optical Society of America, 2014, 31 (11), pp.2415-2428. 〈10.1364/JOSAA.31.002415〉
Liste complète des métadonnées
https://hal-supelec.archives-ouvertes.fr/hal-01108387
Contributeur : Dominique Lesselier <>
Soumis le : jeudi 22 janvier 2015 - 16:10:20
Dernière modification le : jeudi 5 avril 2018 - 12:30:05

Identifiants

Collections

SUPELEC | SUP_LSS | L2S | SUP_DRE | TDS-MACS

Citation

Lorenzo Poli, Giacomo Oliveri, Ping-Ping Ding, Toshifumi Moriyama, Andrea Massa. Multifrequency Bayesian compressive sensing methods for microwave imaging. Journal of the Optical Society of America, Optical Society of America, 2014, 31 (11), pp.2415-2428. 〈10.1364/JOSAA.31.002415〉. 〈hal-01108387〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

238

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD