TY  - RPRT
KW  - Compressive Sensing
KW  -  Inverse Scattering
KW  -  Interval Analysis
KW  -  Evolutionary Optimization
N2  - In this report, an innovative method for the localization of multiple sparse metallic targets is proposed. Starting from the local shape function formulation of the inverse scattering problem and exploiting the multitask Bayesian compressive sensing paradigm, a two-step approach is applied where, after a first estimation of the LSF scattering amplitudes, the reconstruction of the metallic objects is yielded through a thresholding and voting step. The calibration of the BCS parameters together with some preliminary results dealing with small scatterers reported.
A1  - Poli, L.
A1  - Oliveri, G.
A1  - Massa, A.
M1  - technical_report
PB  - University of Trento
AV  - public
TI  - Multi-task Bayesian Compressive Sensing Method for Imaging Sparse Metallic Cylinders
ID  - elediasc12638
Y1  - 2014///
UR  - http://www.eledia.org/students-reports/638/
ER  -