eprintid: 491 rev_number: 4 eprint_status: archive userid: 5 dir: disk0/00/00/04/91 datestamp: 2011-08-02 lastmod: 2013-07-01 11:19:03 status_changed: 2013-07-01 11:19:03 type: techreport metadata_visibility: show item_issues_count: 0 creators_name: Casagranda, Aronne creators_name: Franceschini, Davide creators_name: Benedetti, Manuel creators_name: Massa, Andrea title: Fuzzy-Logic Reasoning for Estimating the Reliability of Noisy Data in Inverse Scattering Problems ispublished: pub subjects: TU full_text_status: public keywords: inverse scattering, fuzzy-logic, iterative multi-scaling approach. 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. date: 2011-01 date_type: published institution: University of Trento department: informaticat refereed: FALSE referencetext: [1] O.M. Bucci and T. Isernia, “Electromagnetic inverse scattering: Retrievable information and measurement strategies,” Radio Science, vol. 32, pp. 2123-2138, Nov.-Dec. 1997. [2] L. A. Zadeh, “Fuzzy Sets”, Information and Control, vol. 8, pp. 338-353, 1965. [3] J. M. Mendel, “Fuzzy logic system for engineer - A tutorial”, Proc. IEEE, vol. 83, pp. 345-377, March 1995. [4] A. Casagranda, D. Franceschini, and A. Massa, “Assessment of the reliability and exploitation of the information content of inverse scattering data through a fuzzy-logic-based strategy - Preliminary results,” IEEE Trans. Geosci. Remote Sensing Lett., vol. 2, pp. 36-39, Jan. 2005. [5] S. Caorsi, M. Donelli, D. Franceschini, and A. Massa, “A New Methodology Based on ad Iterative Multiscaling for Microwave Imaging,” IEEE Trans. Microwave Theory Tech., vol. 51, April 2003. [6] D. Colton and R. Kress, Inverse Acoustic and Electromagnetic Scattering Theory. Springer, Berlin, 1992. [7] R. Azaro, A. Casagranda, D. Franceschini and A. Massa, “An innovative fuzzy-logic-based strategy for an effective exploitation of noisy inverse scattering data”, Progress in Electromagnetics Research, PIERS 54, pp. 283–302. 2005. [8] S. Caorsi, A. Massa, M. Pastorino, and A. Rosani, “Microwave medical imaging: potentialities and limitations of a stochastic optimization technique,”IEEE Trans. Microwave Theory Tech., vol. 52, pp. 1908-1916, Aug. 2004. [9] M. Pastorino, A. Massa, and S. Caorsi, “A microwave inverse scattering technique for image reconstruction based on a genetic algorithm,” IEEE Trans. Instrum. Meas., vol. 49, pp. 573-578, 2000. [10] S Caorsi, M. Donelli, and A. Massa, “Detection, location, and imaging of multiple scatterers by means of the iterative multiscaling method,” IEEE Trans. Microwave Theory Tech., vol. 52, pp. 1217-1228, Apr. 2004. [11] K. Belkebir, S. Bonnard, F. Sabouroux, and M. Saillard, “Validation of 2D inverse scattering algorithms from multi- frequency experimental data,” J. Electromagn. Waves Appl., vol. 14, pp. 1637-1668, Dec. 2000. citation: 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. [Technical Report] document_url: http://www.eledia.org/students-reports/491/1/DISI-11-251.C114.pdf