eprintid: 702
rev_number: 14
eprint_status: archive
userid: 4
dir: disk0/00/00/07/02
datestamp: 2016-03-14 11:14:44
lastmod: 2024-10-15 09:49:03
status_changed: 2016-03-14 11:14:44
type: monograph
metadata_visibility: show
creators_name: Carlin, M.
creators_name: Rocca, P.
creators_name: Oliveri, G.
creators_name: Massa, A.
title: Numerical Analysis of the DoA estimation through BCS
ispublished: pub
subjects: MCS
subjects: MLBE
full_text_status: public
monograph_type: technical_report
keywords: Compressive Sensing, Direction-of-Arrival, Support Vector Machine, Array Synthesis, Inverse Scattering.
abstract: This report deals with the Direction of arrival (DoA) estimation problem formulated within the Bayesian Compressive Sensing (BCS) framework. The performances of a novel method that directly works on the voltages measured at the output of the array elements without requiring the computation of the covariance matrix and that provide accurate and reliable DoAs estimation also without the a-priori knowledge on the number of incident signals have been investigated. The effectiveness of the proposed approach is assessed through an extensive numerical analysis addressing different scenarios, signal configurations, and noise conditions.
date: 2016
publisher: University of Trento
referencetext: [1] M. Carlin, P. Rocca, G. Oliveri, F. Viani, and A. Massa, "Directions-of-arrival estimation through Bayesian Compressive Sensing strategies," IEEE Trans. Antennas Propag., vol. 61, no. 7, pp. 3828-3838, Jul. 2013 (DOI: 10.1109/TAP.2013.2256093).
 
 [2] M. Carlin, P. Rocca, G. Oliveri, and A. Massa, "Bayesian compressive sensing as applied to directions-of-arrival estimation in planar arrays," J. Electr. Comput. Eng. - Special Issue on "Advances in Radar Technologies", vol. 2013, pp. 1-12, 2013 (DOI: 10.1155/2013/245867). 

 [3] M. Carlin, P. Rocca, "A Bayesian compressive sensing strategy for direction-of-arrival estimation," 2012 6th European Conference on Antennas and Propagation (EUCAP), Prague, Czech Republic, 26-30 March, 2012, pp. 1508-1509 (DOI: 10.1109/EuCAP.2012.6206667). 

 [4] L. Lizzi, F. Viani, M. Benedetti, P. Rocca, and A. Massa, "The M-DSO-ESPRIT method for maximum likelihood DoA estimation," Progress in Electromagnetic Research, vol. 80, pp. 477-497, 2008 (DOI: 10.2528/PIER07121106).
 
 [5] M. Donelli, F. Viani, P. Rocca, and A. Massa, "An innovative multi-resolution approach for DoA estimation based on a support vector classification," IEEE Trans. Antennas Propag., vol. 57, no. 8, pp. 2279-2292, Aug. 2009 (DOI: 10.1109/TAP.2009.2024485). 

 [6] L. Lizzi, G. Oliveri, P. Rocca, and A. Massa, "Estimation of the direction-of-arrival of correlated signals by means of a SVM-based multi-resolution approach," 2010 IEEE Antennas and Propagation Society International Symposium, Toronto, ON, Canada, 2010, pp. 1-4, (DOI: 10.1109/APS.2010.5560955). 

 [7] 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). 

 [8] 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 (DOI: 10.1109/TAP.2010.2096400). 

 [9] G. Oliveri, M. Carlin, and A. Massa, "Complex-weight sparse linear array synthesis by Bayesian Compressive Sampling," IEEE Trans. Antennas Propag., vol. 60, no. 5, pp. 2309-2326, May 2012 (DOI: 10.1109/TAP.2012.2189742). 

 [10] 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 (DOI: 10.1109/TAP.2012.2207344). 

 [11] 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 (DOI: 10.1109/TAP.2013.2267195). 

 [12] 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 (DOI: 10.1109/TAP.2013.2287894). 

 [13] 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 (DOI: 10.1109/TAP.2014.2364306). 

 [14] 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). 

 [15] 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). 

 [16] F. Viani, L. Poli, G. Oliveri, F. Robol, and A. Massa, "Sparse scatterers imaging through approximated multitask compressive sensing strategies," Microw. Opt. Technol. Lett., vol. 55, no. 7, pp. 1553-1558, Jul. 2013 (DOI: 10.1002/mop.27612). 

 [17] 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). 

 [18] 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). 

 [19] 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). 

 [20] G. Oliveri, L. Poli, P. Rocca, and A. Massa, "Bayesian compressive optical imaging within the Rytov approximation," Opt. Lett., vol. 37, no. 10, pp. 1760-1762, 2012 (DOI: 10.1364/OL.37.001760). 

 [21] 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).
citation:   Carlin, M. and Rocca, P. and Oliveri, G. and Massa, A.  (2016) Numerical Analysis of the DoA estimation through BCS.  Technical Report. University of Trento.     
document_url: http://www.eledia.org/students-reports/702/1/Numerical_Analysis_of_the_DoA_Estimation_Through_BCS.v2.pdf