eprintid: 778
rev_number: 13
eprint_status: archive
userid: 7
dir: disk0/00/00/07/78
datestamp: 2018-08-03 10:00:30
lastmod: 2024-06-19 21:06:15
status_changed: 2018-08-03 10:00:30
type: monograph
metadata_visibility: show
creators_name: Anselmi, N.
creators_name: Poli, L.
creators_name: Oliveri, G.
creators_name: Massa, A.
title: Integrating the IMSA with Bayesian Compressive Sensing for Solving Inverse Scattering Problems
ispublished: pub
subjects: AWC
subjects: MCS
full_text_status: public
monograph_type: technical_report
keywords: Born approximation (BA), compressive sensing (CS), inverse scattering (IS), Microwave imaging, relevance vector machine (RVM)
abstract: A novel microwave imaging technique is proposed in this work for solving 2D transverse magnetic inverse scattering problems under the first order Born approximation. The developed strategy exploits the well-known regularization capabilities of Bayesian compressive sensing (BCS) and the progressively acquired information through a multi-resolution iterative approach. Towards this end, a customized relevance vector machine (RVM) solver is implemented to iteratively improve the BCS solution accuracy within the identified region of interest (RoI). Selected numerical results are shown to verify the effectiveness of the proposed methodology.
date: 2018
publisher: ELEDIA Research Center - University of Trento
referencetext: 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 (DOI: 10.1109/TGRS.2015.2444391). 
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 (DOI: 10.1109/TGRS.2016.2622061). 
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 (DOI: 10.1016/j.sigpro.2016.06.019). 
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 (DOI: 10.1109/TAP.2015.2444423). 
G. Oliveri, M. Salucci, N. Anselmi, and A. Massa, "Compressive sensing as applied to inverse problems for imaging: theory, applications, current trends, and open challenges," IEEE Antennas Propag. Mag. - Special Issue on "Electromagnetic Inverse Problems for Sensing and Imaging," vol. 59, no. 5, pp. 34-46, Oct. 2017 (DOI: 10.1109/MAP.2017.2731204). 
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 (DOI: 10.1109/MAP.2015.2397092). 
N. Anselmi, L. Poli, G. Oliveri, and A. Massa, "Iterative multi-resolution bayesian CS for microwave imaging," IEEE Trans. Antennas Propag., vol. 66, no. 7, pp. 3665-3677, Jul. 2018 (DOI: 10.1109/TAP.2018.2826574). 
N. Anselmi, G. Oliveri, M. A. Hannan, M. Salucci, and A. Massa, "Color compressive sensing imaging of arbitrary-shaped scatterers," IEEE Trans. Microw. Theory Techn., vol. 65, no. 6, pp. 1986-1999, Jun. 2017 (DOI: 10.1109/TMTT.2016.2645570). 
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 (DOI: 10.1109/TAP.2014.2344673). 
L. Poli, G. Oliveri, and A. Massa, "Imaging sparse metallic cylinders through a local shape function Bayesian compressive sensing approach," J. Opt. Soc. Am. A, vol. 30, no. 6, pp. 1261-1272, 2013 (DOI: 10.1364/JOSAA.30.001261). 
L. Poli, G. Oliveri, F. Viani, and A. Massa, "MT-BCS-based microwave imaging approach through minimum-norm current expansion," IEEE Trans. Antennas Propag., vol. 61, no. 9, pp. 4722-4732, Sep. 2013 (DOI: 10.1109/TAP.2013.2265254). 
F. Viani, L. Poli, G. Oliveri, F. Robol, and A. Massa, "Sparse scatterers imaging through approximated multitask compressive sensing strategies," Microwave Opt. Technol. Lett., vol. 55, no. 7, pp. 1553-1558, Jul. 2013 (10.1002/mop.27612). 
L. Poli, G. Oliveri, P. Rocca, and A. Massa, "Bayesian compressive sensing approaches for the reconstruction of two-dimensional sparse scatterers under TE illumination," IEEE Trans. Geosci. Remote Sens., vol. 51, no. 5, pp. 2920-2936, May 2013 (DOI: 10.1109/TGRS.2012.2218613). 
L. Poli, G. Oliveri, and A. Massa, "Microwave imaging within the first-order Born approximation by means of the contrast-field Bayesian compressive sensing," IEEE Trans. Antennas Propag., vol. 60, no. 6, pp. 2865-2879, Jun. 2012 (DOI: 10.1109/TAP.2012.2194676). 
G. Oliveri, L. Poli, P. Rocca, and A. Massa, "Bayesian compressive optical imaging within the Rytov approximation," Optics Letters, vol. 37, no. 10, pp. 1760-1762, 2012 (DOI: 10.1364/OL.37.001760). 
G. Oliveri, P. Rocca, and A. Massa, "A Bayesian compressive sampling-based inversion for imaging sparse scatterers," IEEE Trans. Geosci. Remote Sens., vol. 49, no. 10, pp. 3993-4006, Oct. 2011 (DOI: 10.1109/TGRS.2011.2128329). 
G. Oliveri, M. Salucci, and N. Anselmi, "Tomographic imaging of sparse low-contrast targets in harsh environments through matrix completion," IEEE Trans. Microw. Theory Tech., vol. 66, no. 6, pp. 2714-2730, Jun. 2018 (DOI: 10.1109/TMTT.2018.2825393). 
M. Salucci, A. Gelmini, L. Poli, G. Oliveri, and A. Massa, “Progressive compressive sensing for exploiting frequency-diversity in GPR imaging,” J.Electromagn. Waves Appl., vol. 32, no. 9, pp. 1164- 1193, 2018 (DOI: 10.1080/09205071.2018.1425160).
citation:   Anselmi, N. and Poli, L. and Oliveri, G. and Massa, A.  (2018) Integrating the IMSA with Bayesian Compressive Sensing for Solving Inverse Scattering Problems.  Technical Report. ELEDIA Research Center - University of Trento.     
document_url: http://www.eledia.org/students-reports/778/1/Integrating_the_IMSA_with_Bayesian_Compressive_Sensing_for_Solving_Inverse_Scattering_Problems.v2.pdf