Fuzzy-Logic Reasoning for Estimating the Reliability of Noisy Data in Inverse Scattering Problems

Casagranda, Aronne and Franceschini, Davide and Benedetti, Manuel and Massa, Andrea (2011) Fuzzy-Logic Reasoning for Estimating the Reliability of Noisy Data in Inverse Scattering Problems. UNSPECIFIED.

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    Abstract

    Inverse scattering data, even though collected in a controlled environment, are usually corrupted by electromagnetic noise, which strongly affects the effectiveness of the reconstruction techniques because of the intrinsic ill-positioning of the problem. In order to limit the effects of the noise on the retrieval procedure and to fully exploit the limited information content available from the measurements, an innovative inversion scheme based on the integration of an adaptive multi-scale procedure and a fuzzy-logic-based decision strategy is proposed. The approach is based on an adaptive, coarse-to-fine successive representation of the unknown object obtained through a sequence of nonlinear reconstructions where suitable weighting coefficients are defined using fuzzy logic. Numerical examples from synthetic and experimental test cases are given to illustrate the advantages brought by the proposed approach in terms of reconstruction quality.

    Item Type: Departmental Technical Report
    Department or Research center: Information Engineering and Computer Science
    Subjects: Q Science > QC Physics (General) > QC661 Electromagnetic Theory
    Q Science > QC Physics (General) > QC760 Electromagnetism
    Uncontrolled Keywords: inverse scattering, fuzzy-logic, iterative multi-scaling approach.
    Report Number: DISI-11-251
    Repository staff approval on: 02 Aug 2011

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