eprintid: 667
rev_number: 8
eprint_status: archive
userid: 4
dir: disk0/00/00/06/67
datestamp: 2015-04-13 08:33:55
lastmod: 2018-02-26 13:40:05
status_changed: 2015-04-13 08:33:55
type: monograph
metadata_visibility: show
creators_name: Poli, L.
creators_name: Oliveri, G.
creators_name: Massa, A.
title: Multi-Task Bayesian Compressive Sensing for microwave imaging exploiting multi-frequency data
ispublished: pub
subjects: MCS
full_text_status: public
monograph_type: technical_report
keywords: Compressive Sensing, Inverse Scattering, Interval Analysis, Array Synthesis
abstract: This report deals with the multi-frequency Multi-Task Bayesian Compressive Sensing (BCS) technique for retrieving the dielectric features of sparse scatterers within an inaccessible investigation domain. A calibration of the MT-BCS method is firstly proposed, before to evaluate the performance of the algorithm on a wide set of scatterer configurations, showing that additional information can be educed from different illumination frequencies to improve the quality of the reconstructions. The impact of the number of frequencies exploited during the reconstruction process on the results is also investigated.
date: 2015
publisher: University of Trento
referencetext: [1] 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.
[2] L. Poli, G. Oliveri, P.-P. Ding, T. Moriyama, and A. Massa, "Multifrequency Bayesian compressive sensing methods for microwave imaging," Journal of the Optical Society of the America A, vol. 31, no. 11, pp. 2415-2428, 2014.
[3] 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.
[4] 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.
[5] 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.
[6] L. Poli, G. Oliveri, P. Rocca, and A. Massa, "Bayesian compressive sensing approaches for the recon- struction of two-dimensional sparse scatterers under TE illumination," IEEE Trans. Geosci. Remote Sensing, vol. 51, no. 5, pp. 2920-2936, May 2013.
[7] 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.
[8] 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.
[9] 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.
[10] G. Oliveri, P.-P. Ding, and L. Poli "3D crack detection in anisotropic layered media through a sparseness- regularized solver," IEEE Antennas Wireless Propag. Lett., in press.
[11] P. Rocca, M. Carlin, L. Manica, and A. Massa, "Microwave imaging within the interval analysis frame- work," Progress in Electromagnetic Research, vol. 143, pp. 675-708, 2013.
[12] P. Rocca, M. Carlin, G. Oliveri, and A. Massa, "Interval analysis as applied to inverse scattering," IEEE International Symposium on Antennas Propag. (APS/URSI 2013), Chicago, Illinois, USA, Jul. 8-14, 2012.
[13] L. Manica, P. Rocca, M. Salucci, M. Carlin, and A. Massa, "Scattering data inversion through interval analysis under Rytov approximation," 7th European Conference on Antennas Propag. (EuCAP 2013), Gothenburg, Sweden, Apr. 8-12, 2013.
[14] P. Rocca, M. Carlin, and A. Massa, "Imaging weak scatterers by means of an innovative inverse scattering technique based on the interval analysis," 6th European Conference on Antennas Propag. (EuCAP 2012), Prague, Czech Republic, Mar. 26-30, 2012.
[15] G. Oliveri and A. Massa, "Bayesian compressive sampling for pattern synthesis with maximally sparse non-uniform linear arrays," IEEE Trans. Antennas Propag., vol. 59, no. 2, pp. 467-481, Feb. 2011.
[16] G. Oliveri, M. Carlin, and A. Massa, "Complex-weight sparse linear array synthesis by Bayesian Com- pressive Sampling," IEEE Trans. Antennas Propag., vol. 60, no. 5, pp. 2309-2326, May 2012.
[17] G. Oliveri, P. Rocca, and A. Massa, "Reliable Diagnosis of Large Linear Arrays - A Bayesian Compressive Sensing Approach," IEEE Trans. Antennas Propag., vol. 60, no. 10, pp. 4627-4636, Oct. 2012.
[18] 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.
[19] G. Oliveri, E. T. Bekele, F. Robol, and A. Massa, "Sparsening conformal arrays through a versatile BCS-based method," IEEE Trans. Antennas Propag., vol. 62, no. 4, pp. 1681-1689, Apr. 2014.
[20] M. Carlin, G. Oliveri, and A. Massa, "Hybrid BCS-deterministic approach for sparse concentric ring isophoric arrays," IEEE Trans. Antennas Propag., vol. 63, no. 1, pp. 378-383, Jan. 2015.
citation:   Poli, L. and Oliveri, G. and Massa, A.  (2015) Multi-Task Bayesian Compressive Sensing for microwave imaging exploiting multi-frequency data.  Technical Report. University of Trento.     
document_url: http://www.eledia.org/students-reports/667/1/Multi-Task%20Bayesian%20Compressive%20Sensing%20for%20microwave%20imaging%20exploiting%20multi-frequency%20data.pdf