• 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