DocumentCode
197494
Title
Experimental characterization of radio tomographic imaging using Tikhonov´s regularization
Author
Ching-Yuih Chiu ; Dujovne, Diego
Author_Institution
Escuela de Inf. y Telecomun., Univ. Diego Portales, Santiago, Chile
fYear
2014
fDate
11-13 June 2014
Firstpage
468
Lastpage
472
Abstract
Radio Tomographic Imaging (RTI) is a new method for tracking and localizing moving objects within an area surrounded by wireless nodes. Signal blockage caused by one or multiple objects (i.e. a person) will attenuate the Received Signal Strength (RSS). In this paper, we experimentally present the limits where RTI may not operate properly, taking into account some of the main parameters such as number of nodes, channel, area, number of pixels, power of transmission and calibration time. Since RTI is an ill-posed problem, we use a simplified linear model using Tikhonov´s regularization for image reconstruction. Kalman filtering allows to keep track of moving objects, hence the average error and its limits.
Keywords
Kalman filters; image reconstruction; inverse problems; object detection; object tracking; sensor placement; tomography; Kalman filtering; RSS; RTI; TIkhonov´s regularization; ill-posed problem; image reconstruction; linear model; moving object localization; moving object tracking; radio tomographic imaging; received signal strength; signal blockage; wireless nodes; Attenuation; Calibration; Kalman filters; Mathematical model; Tomography; Wireless sensor networks; Device-free Localization; Kalman Filter; Radio Tomographic Imaging; Tikhonov´s Regularization; Wireless Sensor Networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Biennial Congress of Argentina (ARGENCON), 2014 IEEE
Conference_Location
Bariloche
Print_ISBN
978-1-4799-4270-1
Type
conf
DOI
10.1109/ARGENCON.2014.6868537
Filename
6868537
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