eprintid: 785
rev_number: 9
eprint_status: archive
userid: 7
dir: disk0/00/00/07/85
datestamp: 2018-10-12 10:21:12
lastmod: 2018-10-12 10:21:12
status_changed: 2018-10-12 10:21:12
type: monograph
metadata_visibility: show
creators_name: Oliveri, G.
creators_name: Salucci, M.
creators_name: Anselmi, N.
title: A Matrix Completion Approach to Image Sparse Targets under the First‐Order Born Approximation
ispublished: pub
subjects: AWC
subjects: MAT
subjects: MCS
full_text_status: public
monograph_type: technical_report
keywords: Born approximation (BA), Bayesian Compressive Sensing (BCS), Inverse Scattering (IS), Matrix Completion (MC)
abstract: In this work, a novel approach to solve the microwave inverse scattering problem under the first-order Born approximation to image sparse and weak targets is addressed. Towards this end, a single-task Bayesian compressive sensing (ST-BCS) solver is exploited to retrieve a preliminary guess of the unknown contrast distribution within an inaccessible domain. Then, a filtering process is used to filter out the "less reliable" contrast coefficients from the BCS guess. Finally, a customized matrix completion (MC) procedure is adopted in order to complete the retrieved images and achieve significant accuracy improvements under high levels of noise on processed data. 
In order to validate the effectiveness of the proposed methodology some representative numerical benchmarks are presented considering different targets and noise levels.
date: 2018
publisher: ELEDIA Research Center - University of Trento
referencetext: L. Poli, G. Oliveri, P. Rocca, and A. Massa, “Bayesian compressive sensing approaches for the reconstruction of two-dimensional sparse scatterers under TE illuminations,” IEEE Trans. Geosci. Remote Sens., vol. 51, no. 5, pp. 2920-2936, May 2013.

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.

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.

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.

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.

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.

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," Journal of Optical Society of America A, vol. 30, no. 6, pp. 1261-1272, 2013.

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.

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, 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.

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, 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.

M. Salucci, A. Gelmini, L. Poli, G. Oliveri, and A. Massa, “Progressive compressive sensing for exploiting frequency-diversity in GPR imaging,” Journal of Electromagnetic Waves and Applications, vol. 32, no. 9, pp. 1164- 1193, 2018 (DOI: 10.1080/09205071.2018.1425160).
citation:   Oliveri, G. and Salucci, M. and Anselmi, N.  (2018) A Matrix Completion Approach to Image Sparse Targets under the First‐Order Born Approximation.  Technical Report. ELEDIA Research Center - University of Trento.     
document_url: http://www.eledia.org/students-reports/785/1/A%20%20Matrix%20Completion%20Approach%20to%20Image%20Sparse%20Targets%20under%20the%20First%E2%80%90Order%20Born%20Approximation.pdf