eprintid: 312 rev_number: 4 eprint_status: archive userid: 5 dir: disk0/00/00/03/12 datestamp: 2011-07-29 lastmod: 2013-06-28 11:16:09 status_changed: 2013-06-28 11:16:09 type: techreport metadata_visibility: show item_issues_count: 0 creators_name: Donelli, Massimo creators_name: Azaro, Renzo creators_name: Lizzi, Leonardo creators_name: Viani, Federico creators_name: Massa, Andrea title: A SVM-Based Multi-Resolution Procedure for the Estimation of the DOAS of Interfering Signals in a Communication System ispublished: pub subjects: TU full_text_status: public abstract: In this work, the use of a planar antenna system for the estimation of the directions of arrivals (DOAs) of multiple signals impinging on the receiver has been considered. Towards this end, an efficient multi-resolution method based on a SVM-classifier is proposed for determining a probabilitic map of the DOAs of the unknown interfering signals. Numerical results dealing with multiple interferers scenarios in noisy environments are provided in order to assess the feasibility as well as the capability of the proposed approach. date: 2011-01 date_type: published institution: University of Trento department: informaticat refereed: FALSE referencetext: [1] S. P. Applebaum, “Adaptive arrays,” IEEE Trans. Antennas Propagat, vol. AP-24, pp. 585-598, May 1976. [2] R. O. Schimid, “Multiple emitter location and signal parameter estimation,” IEEE Trans. Antennas Propagat, vol. 34, pp. 3226-3231, 1986. [3] A. Swindlehurst, T. Kaliath, “A performance analysis of sub space-based methods in the presence of model errors. I. The MUSIC algorithm,” IEEE Trans.on Sign. Processing, vol. 40, pp. 1578-1774, 1992. [4] F. Gao, B. Gershman, “A generalized ESPRIT approach to direction of arrival estimation,” IEE Signal Processing Letters,vol. 12, pp. 254-257, 2005. [5] A. H. El Zoogli, C. G. Christodoulou, and M. Georgiopulos, “A neural network-based smart antenna for multiple source tracking,” IEEE Trans. Antennas Propagat., vol. 48, pp. 768-776, May 2000. [6] V.Vapnik, Statistical Learning Theory. New York: Wiley, 1998. [7] E. Bermani, A. Boni, S. Caorsi, M. Donelli, and A. Massa, “A multi-source strategy based on a learning-by- examples technique for buried object detection,” Progress In Electromagnetic Research, PIER 48, pp. 185-200, 2004. [8] D. S. Weile and E. Michielssen, “The control of adaptive antenna arrays with genetic algorithms using dominances and diploidy,” IEEE Trans. Antennas Propagat, vol. 49, pp. 1424-1433, Oct. 2003. citation: Donelli, Massimo and Azaro, Renzo and Lizzi, Leonardo and Viani, Federico and Massa, Andrea (2011) A SVM-Based Multi-Resolution Procedure for the Estimation of the DOAS of Interfering Signals in a Communication System. [Technical Report] document_url: http://www.eledia.org/students-reports/312/1/DISI-11-245.C120.pdf