eprintid: 742
rev_number: 13
eprint_status: archive
userid: 7
dir: disk0/00/00/07/42
datestamp: 2017-07-28 15:46:06
lastmod: 2024-05-13 08:35:31
status_changed: 2017-07-28 15:46:06
type: monograph
metadata_visibility: show
creators_name: Anselmi, N.
creators_name: Oliveri, G.
creators_name: Hannan, M.
creators_name: Salucci, M.
creators_name: Massa, A.
title: Innovative Alphabet‐Based Bayesian Compressive Sensing Technique for Imaging Targets with Arbitrary Shape
ispublished: pub
subjects: AWC
subjects: MCS
full_text_status: public
monograph_type: technical_report
keywords: Inverse Scattering (IS), Bayesian Compressive Sensing (BCS), Microwave Imaging, First Order Born Approximation
abstract: In this work an innovative two-dimensional (2D) microwave imaging technique exploiting Bayesian Compressive Sensing (BCS) and a wavelet-based alphabet for representing the problem unknowns is dealt with. The proposed approach is based on the generalization of the sparsity concept, extending the range of applicability of BCS-based inverse scattering (IS) techniques to objects with arbitrary shape and dimensions. A set of BCS reconstructions is performed considering different expansion bases in the alphabet, without the need for a-priori knowledge about the unknown scatterers. Then, the best reconstruction is recognized as that minimizing the number of non-null retrieved coefficients (i.e., the sparsest one). In order to verify the effectiveness of the proposed imaging technique, a set of representative numerical benchmarks is presented. Some comparisons with state-of-the-art IS techniques are presented, as well.
date: 2017
publisher: ELEDIA Research Center - University of Trento
referencetext: 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.

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.

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.

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.

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.

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.

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.

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, March 2017.

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.

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.

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.

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.

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.

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.

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.

F. Viani, G. Oliveri, and A. Massa, “Compressive sensing pattern matching techniques for synthesizing planar sparse arrays,” IEEE Trans. Antennas Propag., vol. 61, no. 9, pp. 4577-4587, Sept. 2013.

G. Oliveri, M. Salucci, and A. Massa, “Synthesis of modular contiguously clustered linear arrays through a sparseness-regularized solver,” IEEE Trans. Antennas Propag., vol. 64, no. 10, pp. 4277-4287, Oct. 2016.

P. Rocca, M. A. Hannan, M. Salucci, and A. Massa, “Single-snapshot DoA estimation in array antennas with mutual coupling through a multi-scaling BCS strategy,” IEEE Trans. Antennas Propag., vol. 65, no. 6, pp. 3203-3213, Jun. 2017.

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.

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.
citation:   Anselmi, N. and Oliveri, G. and Hannan, M. and Salucci, M. and Massa, A.  (2017) Innovative Alphabet‐Based Bayesian Compressive Sensing Technique for Imaging Targets with Arbitrary Shape.  Technical Report. ELEDIA Research Center - University of Trento.     
document_url: http://www.eledia.org/students-reports/742/1/Innovative_Alphabet%E2%80%90Based_Bayesian_Compressive_Sensing_Technique_for_Imaging_Targets_with_Arbitrary_Shape.v2.pdf