eprintid: 665 rev_number: 7 eprint_status: archive userid: 4 dir: disk0/00/00/06/65 datestamp: 2014-11-06 09:58:33 lastmod: 2014-11-06 09:58:33 status_changed: 2014-11-06 09:58:33 type: thesis metadata_visibility: show creators_name: Santacatterina, G. title: Tolerance analysis in sub-arrayed antennas by means of a probabilistic methodology based on interval arithmetic ispublished: pub subjects: MCS full_text_status: public keywords: Compressive Sensing, Inverse Scattering abstract: Sub-arraying techniques are commonly used in the synthesis of array antennas, especially for large arrays since they allow to group the elements into sub-arrays reducing the number of control points in the feeding network. The reduction in the complexity of the antenna architecture allows a significant decrease in costs and a simplification in array manufacturing. Calibration operations should be theoretically simplified, as well, because of the reduced number of control points to be handle, but random errors still remain difficult to identify and correct. Recently, Interval Analysis (IA)-based methods have been developed to predict the effects of uncertainties in amplitude values, arising from the non-ideality of the electronic components, on the radiation pattern. However, such approaches assign the same probability (i.e., a uniform probability distribution) for each value within the tolerance interval. This project is aimed to propose a novel approach aimed at dealing with sub-arrayed architectures by taking into account Gaussian probability distribution functions modelling the statistical behavior of the amplitude deviations with respect to the nominal value of the amplifiers. date: 2014-10-01 date_type: published institution: University of Trento department: ELEDIA Research Center @ DISI thesis_type: masters referencetext: [1] 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. [2] 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. [3] 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. [4] 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. [5] 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 Sensing, vol. 51, no. 5, pp. 2920-2936, May. 2013. [6] 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. [7] G. Oliveri, P. Rocca, and A. Massa, "A bayesian compressive sampling-based inversion for imaging sparse scatterers," IEEE Trans. Geosci. Remote Sensing, vol. 49, no. 10, pp. 3993-4006, Oct. 2011. [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, Sept. 2013. [10] G. Oliveri, L. Lizzi, M. Pastorino, and A. Massa, "A nested multi-scaling inexact-Newton iterative approach for microwave imaging," IEEE Trans. Antennas Propag., vol. 60, no. 2, pp. 971-983, Feb. 2012. [11] G. Oliveri, A. Randazzo, M. Pastorino, and A. Massa, "Electromagnetic imaging within the contrast-source formulation by means of the multiscaling inexact Newton method," Journal of Optical Society of America A, vol. 29, no. 6, pp. 945-958, 2012. [12] M. Salucci, D. Sartori, N. Anselmi, A. Randazzo, G. Oliveri, and A. Massa, “Imaging buried objects within the second-order Born approximation through a multiresolution-regularized inexact-Newton method”, in 2013 International Symposium on Electromagnetic Theory (EMTS), (Hiroshima, Japan), pp. 116-118, May 20-24 2013. citation: Santacatterina, G. (2014) Tolerance analysis in sub-arrayed antennas by means of a probabilistic methodology based on interval arithmetic. Masters thesis, University of Trento. document_url: http://www.eledia.org/students-reports/665/1/Abstract.A613.pdf