eprintid: 728 rev_number: 9 eprint_status: archive userid: 4 dir: disk0/00/00/07/28 datestamp: 2017-04-20 07:14:15 lastmod: 2018-02-26 14:54:24 status_changed: 2017-04-20 07:14:15 type: monograph metadata_visibility: show creators_name: Salucci, M. creators_name: Poli, L. creators_name: Massa, A. title: Deterministic Inversion of Wideband GPR Data for Multiā€Resolution Imaging of Buried Objects 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 conjugate-gradient (CG)-based deterministic microwave imaging technique are assessed for the inversion of wideband ground penetrating radar (GPR) data. The developed methodology exploits the intrinsic frequency diversity of GPR measurements through a multi-frequency (MF) strategy in order to add information to the inversion problem and to mitigate the negative effects of ill-posedness of the buried inverse scattering (IS) problem. Moreover, the iterative multi-scaling approach (IMSA) is exploited in order to increase as much as possible the ratio between non-redundant data and problem unknowns, thus mitigating the problem of the non-linearity. Some numerical results are shown, in order to analyze the achievable reconstruction capabilities by the developed MF technique when dealing with the retrieval of objects having different values of relative permittivity. A direct comparison with a frequency hopping (FH)-based implementation of the same multi-resolution deterministic solver is shown, as well, to highlight the differences between the two approaches. date: 2017 publisher: University of Trento referencetext: [1] P. Rocca, M. Benedetti, M. Donelli, D. Franceschini, and A. Massa, "Evolutionary optimization as applied to inverse problems," Inverse Probl., vol. 25, pp. 1-41, Dec. 2009. [2] P. Rocca, G. Oliveri, and A. Massa, "Differential Evolution as applied to electromagnetics," IEEE Antennas Propag. Mag., vol. 53, no. 1, pp. 38-49, Feb. 2011. [3] M. Salucci, G. Oliveri, and A. Massa, "GPR prospecting through an inverse scattering frequency-hopping multi-focusing approach," IEEE Trans. Geosci. Remote Sens., vol. 53, no. 12, pp. 6573-6592, Dec. 2015. [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. [5] A. Massa, P. Rocca, and G. Oliveri, "Compressive sensing in electromagnetics - A review," IEEE Antennas Propag. Mag., pp. 224-238, vol. 57, no. 1, Feb. 2015. [6] A. Massa and F. Texeira, Guest-Editorial: Special Cluster on Compressive Sensing as Applied to Electromagnetics, IEEE Antennas Wireless Propag. Lett., vol. 14, pp. 1022-1026, 2015. [7] N. Anselmi, G. Oliveri, M. Salucci, and A. Massa, "Wavelet-based compressive imaging of sparse targets," IEEE Trans. Antennas Propag., vol. 63, no. 11, pp. 4889-4900, Nov. 2015. [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. [11] F. Viani, L. Poli, G. Oliveri, F. Robol, and A. Massa, "Sparse scatterers imaging through approximated multi-task compressive sensing strategies," Microw. Opt. Technol. Lett., vol. 55, no. 7, pp. 1553-1557, Jul. 2013. [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. (2017) Deterministic Inversion of Wideband GPR Data for Multiā€Resolution Imaging of Buried Objects. Technical Report. University of Trento. document_url: http://www.eledia.org/students-reports/728/1/Deterministic%20Inversion%20of%20Wideband%20GPR%20Data%20for%20Multi%E2%80%90Resolution%20Imaging%20of%20Buried%20Objects.pdf