TY  - RPRT
AV  - public
KW  - Compressive Sensing
KW  -  Inverse Scattering
KW  -  Interval Analysis
PB  - University of Trento
A1  - Poli, L.
A1  - Oliveri, G.
A1  - Viani, F.
A1  - Massa, A.
ID  - elediasc12658
M1  - technical_report
N2  - In this report, an innovative three-step contrast-source probabilistic technique is proposed for the reconstruction of image 2D-sparse dielectric profiles. Within the formulation of the inverse scattering problem, such an approach combines (i) a SVD-based step to retrieve the minimum-norm currents, (ii) a probabilistic reformulation of the inverse scattering problem in terms of the real and imaginary parts of the sparse contrast currents (iii) a multi-task BCS strategy for properly correlating the unknown variables (real and imaginary parts of contrast source coefficients). An enhanced version of the multi-task implementation that takes into account the correlations real and imaginary parts of contrast source coefficients related to different views is also investigated through a wide set of numerical experiments.
TI  - Multi-task Bayesian Compressive Sensing for microwave imaging exploiting the minimum-norm current formulation
Y1  - 2014///
UR  - http://www.eledia.org/students-reports/658/
ER  -