eprintid: 735
rev_number: 9
eprint_status: archive
userid: 4
dir: disk0/00/00/07/35
datestamp: 2017-06-15 07:14:20
lastmod: 2018-02-26 15:55:08
status_changed: 2017-06-15 07:14:20
type: monograph
metadata_visibility: show
creators_name: Salucci, M.
creators_name: Poli, L.
creators_name: Anselmi, N.
creators_name: Massa, A.
title: Microwave Imaging of Buried Objects having Different Permittivities through an Innovative Multi-Frequency Stochastic Method
ispublished: pub
subjects: AWC
subjects: MEA
full_text_status: public
monograph_type: technical_report
keywords: Ground Penetrating Radar (GPR), Inverse Scattering (IS), Multi-Frequency (MF), Particle Swarm Optimization (PSO), Stochastic Optimization, Wide-band Data, Iterative Multi Scaling Approach (IMSA) 
abstract: This work deals with the retrieval of the electromagnetic characteristics of inaccessible subsurface domains by processing ground penetrating radar (GPR) data. Assuming a multi-frequency (MF) formulation of the buried inverse scattering problem, the solution is obtained by means of a multi-resolution particle swarm optimization (PSO) algorithm. The developed MF-IMSA-PSO method is able to proficiently exploit the intrinsic frequency diversity of wideband GPR measurements in order to mitigate the ill-posedness and non-linearity issues of the subsurface inverse scattering problem. Moreover, thanks to the integration of the PSO within the iterative multi-scaling approach (IMSA) an increased resolution of the retrieved images is obtained within the identified regions of interest, where the buried objects are supposed to lie. Some numerical experiments are shown in order to assess the effectiveness, the robustness to noise, as well as the current limitations, of the developed method in retrieving buried scatterers having different levels of electric permittivity (i.e., different levels of contrast with respect to the surrounding background medium). Moreover, a direct comparison with respect to the MF-IMSA-CG, a state-of-the-art approach based on a conjugate gradient (CG) local search algorithm, is given.
date: 2016
publisher: University of Trento
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[15] M. Donelli, D. Franceschini, P. Rocca, and A. Massa, "Three-dimensional microwave imaging problems solved through an efficient multiscaling particle swarm optimization," IEEE Trans. Geosci. Remote Sensing, vol. 47, no. 5, pp. 1467-1481, May 2009.
citation:   Salucci, M. and Poli, L. and Anselmi, N. and Massa, A.  (2016) Microwave Imaging of Buried Objects having Different Permittivities through an Innovative Multi-Frequency Stochastic Method.  Technical Report. University of Trento.     
document_url: http://www.eledia.org/students-reports/735/1/Microwave%20Imaging%20of%20Buried%20Objects%20having%20Different%20Permittivities%20through%20an%20Innovative%20Multi%E2%80%90Frequency%20Stochastic%20Method.pdf