An innovative three-step technique based on the multi-task Bayesian compressive sensing (MT – BCS) strategy is introduced to image 2D-sparse dielectric profiles. The proposed approach reformulates the contrast source mathematical description of the inversion problem into two fictitious real-valued ones jointly solved through a fast Relevance Vector Machine by taking into account the inter-relationships between the real and the imaginary parts of the unknown equivalent currents. Selected results from a numerical validation are presented and discussed to comparatively assess the accuracy, the robustness, and the computational efficiency of the proposed implementation
MT-BCS -based Microwave Imaging Approach through Minimum-Norm Current Expansion / Poli, Lorenzo; Oliveri, Giacomo; Viani, Federico; Massa, Andrea. - In: IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION. - ISSN 0018-926X. - STAMPA. - 61:9(2013), pp. 4722-4732. [10.1109/TAP.2013.2265254]
MT-BCS -based Microwave Imaging Approach through Minimum-Norm Current Expansion
Poli, Lorenzo;Oliveri, Giacomo;Viani, Federico;Massa, Andrea
2013-01-01
Abstract
An innovative three-step technique based on the multi-task Bayesian compressive sensing (MT – BCS) strategy is introduced to image 2D-sparse dielectric profiles. The proposed approach reformulates the contrast source mathematical description of the inversion problem into two fictitious real-valued ones jointly solved through a fast Relevance Vector Machine by taking into account the inter-relationships between the real and the imaginary parts of the unknown equivalent currents. Selected results from a numerical validation are presented and discussed to comparatively assess the accuracy, the robustness, and the computational efficiency of the proposed implementationFile | Dimensione | Formato | |
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