Anselmi, N. and Oliveri, G. and Hannan, M. and Salucci, M. and Massa, A. (2017) An Innovative BCS‐Based Microwave Imaging Technique for Imaging Unknown Objects With Arbitrary Size and Shape. Technical Report. ELEDIA Research Center - University of Trento.
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Abstract
This work presents a numerical validation of an innovative two-dimensional (2D) microwave inverse scattering technique exploiting Bayesian Compressive Sensing (BCS) and a dictionary of wavelet-based expansion bases. The goal of the dictionary-based BCS is to provide faithful guesses of the dielectric distribution inside the imaged scenario even if the unknown objects inside it are not sparse in the standard pixel basis. The developed strategy is based on a two-level hierarchical application of the BCS algorithm. In the first step, several sparsity-regularized inversions are performed using the dictionary of candidate bases. In the second step, the retrieved vectors are compared and the sparsest reconstruction is selected. Some numerical results are shown, in order to verify the effectiveness of the developed microwave imaging technique. Moreover, some illustrative results are shown to compare its performance with respect to competitive state-of-the-art alternatives.
| Item Type: | Monograph (Technical Report) |
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| Uncontrolled Keywords: | Inverse Scattering (IS), Bayesian Compressive Sensing (BCS), Microwave Imaging, First Order Born Approximation |
| Subjects: | A Areas > A WC Next Generation Wireless Communications M Methodologies > M CS Compressive Sensing |
| URI: | http://www.eledia.org/students-reports/id/eprint/744 |
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