• DocumentCode
    177398
  • Title

    Spatio-temporal sampling and reconstruction of diffusion fields induced by point sources

  • Author

    Murray-Bruce, John ; Dragotti, Pier Luigi

  • Author_Institution
    Electr. & Electron. Eng. Dept., Imperial Coll. London, London, UK
  • fYear
    2014
  • fDate
    4-9 May 2014
  • Firstpage
    31
  • Lastpage
    35
  • Abstract
    In this paper we consider a diffusion field induced by multiple point sources and address the problem of reconstructing the field from its spatio-temporal samples obtained using a sensor network. We begin by formulating the problem as a multi-source estimation problem - so estimating source locations, activation times and intensities given samples of the induced field. Next a two-step algorithm is proposed for the single (localized and instantaneous) source field. First, the source location and intensity are estimated by applying the “reciprocity gap” principle; we show that this step can also reveal locations of multiple non-instantaneous sources. In the second step, we use an iterative method, based on Cauchy-Schwarz inequality, to find the activation time given the estimated location and intensity. Finally we extend this algorithm to the multi-source field and present simulation results to validate our findings.
  • Keywords
    estimation theory; iterative methods; signal reconstruction; signal sampling; Cauchy-Schwarz inequality; activation times; diffusion fields; iterative method; multisource estimation problem; multisource field; point sources; reciprocity gap; sensor network; source intensity; source locations; spatiotemporal reconstruction; spatiotemporal sampling; Acoustics; Conferences; Equations; Estimation; Mathematical model; Speech; Time measurement; Prony´s method; Spatio-temporal sampling; diffusion process; reciprocity gap; sensor network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/ICASSP.2014.6853552
  • Filename
    6853552