Poli, L. and Oliveri, G. and Viani, F. and Massa, A. (2014) Multi-task Bayesian Compressive Sensing for microwave imaging exploiting the minimum-norm current formulation. Technical Report. University of Trento.
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Multi-task Bayesian Compressive Sensing for microwave imaging exploiting the minimum-norm current formulation.pdf Download (18MB) | Preview |
Abstract
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.
| Item Type: | Monograph (Technical Report) |
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| Uncontrolled Keywords: | Compressive Sensing, Inverse Scattering, Interval Analysis |
| Subjects: | M Methodologies > M CS Compressive Sensing |
| URI: | http://www.eledia.org/students-reports/id/eprint/658 |
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