A novel method based on the contrast field formulation for imaging sparse scatterers is proposed in this paper. The inversion of the scattering data is achieved by means of a Bayesian Compressive Sensing (BCS)-based methodology developed within an iterative procedure where the non-linear problem is recast as a sequence of linear problems solved through a Relevance Vector Machine (RVM). Selected numerical examples are illustrated in order to evaluate the effectiveness of the presented approach, also in a comparative fashion with a state-of-the-art (SoA) BCS-based method based on the first order Born approximation,
Sensing dielectric scatterers by means of the born iterative method in the contrast-field Bayesian compressive sensing framework / Salucci, M.; Oliveri, G.; Massa, A.. - STAMPA. - (2018), pp. 1-4. (Intervento presentato al convegno CAMA 2018 tenutosi a Vasteras, Sweden nel 3rd-6th September 2018) [10.1109/CAMA.2018.8530590].
Sensing dielectric scatterers by means of the born iterative method in the contrast-field Bayesian compressive sensing framework
Salucci M.;Oliveri G.;Massa A.
2018-01-01
Abstract
A novel method based on the contrast field formulation for imaging sparse scatterers is proposed in this paper. The inversion of the scattering data is achieved by means of a Bayesian Compressive Sensing (BCS)-based methodology developed within an iterative procedure where the non-linear problem is recast as a sequence of linear problems solved through a Relevance Vector Machine (RVM). Selected numerical examples are illustrated in order to evaluate the effectiveness of the presented approach, also in a comparative fashion with a state-of-the-art (SoA) BCS-based method based on the first order Born approximation,File | Dimensione | Formato | |
---|---|---|---|
Sensing dielectric scatterers by means of the Born iterative method in the contrast-field Bayesian compressive sensing framework.pdf
Solo gestori archivio
Tipologia:
Versione editoriale (Publisher’s layout)
Licenza:
Tutti i diritti riservati (All rights reserved)
Dimensione
657.25 kB
Formato
Adobe PDF
|
657.25 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione