eprintid: 730
rev_number: 9
eprint_status: archive
userid: 4
dir: disk0/00/00/07/30
datestamp: 2017-05-04 06:46:03
lastmod: 2018-02-26 15:53:58
status_changed: 2017-05-04 06:46:03
type: monograph
metadata_visibility: show
creators_name: Salucci, M.
creators_name: Poli, L.
creators_name: Massa, A.
title: Microwave Imaging of Buried Targets through a Multi-Zooming Approach: Reconstruction Capabilities for Different Object Conductivities
ispublished: pub
subjects: AWC
subjects: MDSCP
full_text_status: public
monograph_type: technical_report
keywords: Ground Penetrating Radar (GPR), Inverse Scattering (IS), Multi-Frequency, Conjugate Gradient, Deterministic Approaches, Wide-band Data  
abstract: In this work, the performance of an innovative microwave imaging methodology for buried object detection are analyzed. More precisely, the developed inverse scattering (IS) approach is based on a Multi-Frequency (MF) formulation of the buried IS equations in order to exploit the frequency diversity coming from wideband ground penetrating radar (GPR) measurements. The arising MF cost function is minimized through a customized deterministic solver based on a conjugate gradient (CG) minimizer nested within the iterative multi-scaling approach (IMSA) for achieving higher resolutions in the identified regions of interest (RoIs). Some illustrative numerical results are shown, in order to verify the effectiveness of the developed MF-IMSA-CG methodology when dealing with the retrieval of buried objects having different values of electric conductivity. For completeness, as well as for the sake of comparison, the reconstructions yielded by a competitive state-of-the-art approach based on a frequency hopping (FH) processing of the GPR spectrum are also shown, by considering several noise conditions.
date: 2016
publisher: University of Trento
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[4] M. Salucci, L. Poli, N. Anselmi and A. Massa, "Multifrequency particle swarm optimization for enhanced multiresolution GPR microwave imaging," IEEE Trans. Geosci. Remote Sens., vol. 55, no. 3, pp. 1305-1317, Mar. 2017.
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[8] G. Oliveri, N. Anselmi, and A. Massa, "Compressive sensing imaging of non-sparse 2D scatterers by a total-variation approach within the Born approximation," IEEE Trans. Antennas Propag., vol. 62, no. 10, pp. 5157-5170, Oct. 2014.
[9] T. Moriyama, G. Oliveri, M. Salucci, and T. Takenaka, "A multi-scaling forward-backward time-stepping method for microwave imaging," IEICE Electron. Expr., vol. 11, no. 16, pp. 1-12, Aug. 2014.
[10] T. Moriyama, M. Salucci, M. Tanaka, and T. Takenaka, "Image reconstruction from total electric field data with no information on the incident field," J. Electromagnet. Wave., vol. 30, no. 9, pp. 1162-1170, 2016.
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[12] M. Salucci, L. Poli, and A. Massa, "Advanced multi-frequency GPR data processing for non-linear deterministic imaging," Signal Processing - Special Issue on 'Advanced Ground-Penetrating Radar Signal-Processing Techniques,' vol. 132, pp. 306-318, Mar. 2017.
[13] M. Salucci, N. Anselmi, G. Oliveri, P. Calmon, R. Miorelli, C. Reboud, and A. Massa, "Real-time NDT-NDE through an innovative adaptive partial least squares SVR inversion approach," IEEE Trans. Geosci. Remote Sens., vol. 54, no. 11, pp. 6818-6832, Nov. 2016.
[14] L. Poli, G. Oliveri, and A. Massa, "Imaging sparse metallic cylinders through a local shape function bayesian compressing sensing approach," J. Opt. Soc. Am. A, vol. 30, no. 6, pp. 1261-1272, Jun. 2013.
citation:   Salucci, M. and Poli, L. and Massa, A.  (2016) Microwave Imaging of Buried Targets through a Multi-Zooming Approach: Reconstruction Capabilities for Different Object Conductivities.  Technical Report. University of Trento.     
document_url: http://www.eledia.org/students-reports/730/1/Microwave%20Imaging%20of%20Buried%20Targets%20through%20a%20Multi%E2%80%90Zooming%20Approach_%20Reconstruction%20Capabilities%20for%20Different%20Object%20Conductivities.pdf