eprintid: 520
rev_number: 4
eprint_status: archive
userid: 5
dir: disk0/00/00/05/20
datestamp: 2011-06-30
lastmod: 2013-06-30 09:12:56
status_changed: 2013-06-30 09:12:56
type: techreport
metadata_visibility: show
item_issues_count: 0
creators_name: Viani, Federico
creators_name: Rocca, Paolo
creators_name: Benedetti, Manuel
creators_name: Oliveri, Giacomo
creators_name: Massa, Andrea
title: Electromagnetic passive localization and tracking of moving targets in a WSN-infrastructured environment.
ispublished: pub
subjects: TU
full_text_status: public
abstract: In this paper, an innovative strategy for the passive localization of transceiver-free objects is presented. The localization is yielded by processing the received signal strength data measured in an infrastructured environment. The problem is reformulated in terms of an inverse source one, where the probability map of the presence of an equivalent source modeling the moving target is looked for. Toward this end, a customized classification procedure based on a support vector machine is exploited. Selected, but representative, experimental results are reported to assess the feasibility of the proposed approach and to show the potentialities and applicability of this passive and unsupervised technique. “(c) Institute of Physics”
date: 2011-01
date_type: published
institution: University of Trento
department: informaticat
refereed: TRUE
referencetext: [1] Chong C-Y and Kumar S P 2003 Sensor networks: evolution, opportunities, and challenges Proc. IEEE 91 1247-56 [2] Li Z, Dehaene W and Gielen G 2009 A 3-tier UWB-based indoor localization system for ultra-low-power sensor networks IEEE Trans. Wirel. Commun. 8 2813-8 [3] Latsoudas G and Sidiropoulos N D 2007 A fast and effective multidimensional scaling approach for node localization in wireless sensor networks IEEE Trans. Geosci. Remote Sens. 55 5121-7 [4] Huang C-T, Wu C-H, Lee Y-N and Chen J-T 2009 A novel indoor RSS-based position location algorithm using factor graphs IEEE Trans. Wirel. Commun. 8 3050-8 [5] Pahlavan K, Li X and Makela J P 2002 Indoor geolocation science and technology IEEE Commun. Mag. 40 112-8 [6] Catovic A and Sahinoglu Z 2004 The Cramer-Rao bounds of hybrid TOA/RSS and TDOA/RSS location estimation schemes IEEE Commun. Lett. 8 626-8 [7] Li X 2006 RSS-based location estimation with unknown pathloss model IEEE Trans. Wirel. Commun. 5 3626-33 [8] Li X 2007 Collaborative localization with received-signal strength in wireless sensor networks IEEE Trans. Veh. Technol. 56 3807-17 [9] Cabrera-Mora F and Xiao J 2008 Preprocessing technique to signal strength data of wireless sensor network for real-time distance estimation Proc. IEEE Int. Conf. Robotics Automation (ICRA) (Pasadena, CA, USA, 19-23 May 2008) pp 1537-42 [10] Saxena M, Gupta P and Jain B N 2008 Experimental analysis of RSSI-based location estimation in wireless sensor networks Proc. IEEE Conf. Commun. System Software and Middleware (COMSWARE) (Bangalore, India, Jan 2008) pp 503-10 [11] Butler W 2008 Design considerations for intrusion detection wide area surveillance radars for perimeters and borders Proc. IEEE Int. Conf. Tech. Homeland Security (Waltham, MA, USA, 12-13 May 2008) pp 47-50 [12] Bugaev A S, Chapurski V V, Ivashov S I, Razevig V V, Sheiko A P and Vasilyev I A 2004 Through wall sensing of human breathing and heart beating by monochromatic radar 2004 Proc. Int. Conf. on Ground Penetrating Radar (Delft, the Netherlands, 21-24 June 2004) vol 1 pp 291-4 [13] Withington P, Fluhler H and Nag S 2003 Enhancing homeland security with advanced UWB sensors IEEE Microw. Mag. 4 51-8 [14] Viani F, Lizzi L, Rocca P, Benedetti M, Donelli M and Massa A 2008 Object tracking through RSSI measurements in wireless sensor networks Electron. Lett. 44 653-4 [15] El Zooghby A H, Christodoulou C G and Georgiopulos M 2000 A neural network-based smart antenna for multiple source tracking IEEE Trans. Antennas Propag. 48 768-76 [16] Donelli M, Viani F, Rocca P and Massa A 2009 An innovative multiresolution approach for DOA estimation based on a support vector classification IEEE Trans. Antennas Propag. 57 2279-92 [17] Massa A, Boni A and Donelli M 2005 A classification approach based on SVM for electromagnetic subsurface sensing IEEE Trans. Geosci. Remote Sens. 43 2084-93 [18] Liu Q, Liao X and Carin L 2008 Detection of unexploded ordnance via efficient semisupervised and active learning IEEE Trans. Geosci. Remote Sens. 46 2558-67 [19] Pasolli E, Melgani F and Donelli M 2009 Gaussian process approach to buried object size estimation in GPR images IEEE Geosci. Remote Sens. Lett. 7 141-5 [20] Viani F, Meaney P, Rocca P, Azaro R, Donelli M, Oliveri G and Massa A 2009 Numerical validation and experimental results of a multi-resolution SVM-based classification procedure for breast imaging Proc. IEEE Antennas Propag. Symp. (Charleston, SC, USA, 1-5 June 2009) pp 1-4 [21] Chew W C 1990 Waves and Fields in Inhomogeneous Media (New York: Wiley) (ISBN: 978-0-7803-4749-6) [22] Ishimaru A 1996 Electromagnetic Wave Propagation, Radiation, and Scattering (Englewood Cliffs, NJ: Prentice-Hall) (ISBN: 0132490536) [23]Vapnik V 1998 Statistical Learning Theory (New York: Wiley) (ISBN: 978-0-471-03003-4) [24] Morik K, Brockhausen P and Joachims T 1999 Combining statistical learning with a knowledge-based approach-a case study in intensive care monitoring Proc. Int. Conf. Mach. Learn. (ICML 1999) (Bled, Slovenia, 27-30 June 1999) pp 268-77 (ISBN: 1-55860-612-2)
citation:   Viani, Federico and Rocca, Paolo and Benedetti, Manuel and Oliveri, Giacomo and Massa, Andrea  (2011) Electromagnetic passive localization and tracking of moving targets in a WSN-infrastructured environment.  [Technical Report]     
document_url: http://www.eledia.org/students-reports/520/1/DISI-11-100-R191.pdf