• DocumentCode
    107322
  • Title

    Advanced S ^2 Imaging: Application of Multivariate Statistical Analysis to Spatially and Spectrally Resolved Datasets

  • Author

    Sevigny, Benoit ; Le Cocq, Guillaume ; Carrero, Carmen Carina Castineiras ; Valentin, Constance ; Sillard, P. ; Bouwmans, Geraud ; Bigot, Laurent ; Quiquempois, Yves

  • Author_Institution
    Lab. de Phys. des Lasers, Univ. Lille 1, Villeneuve d´Ascq, France
  • Volume
    32
  • Issue
    23
  • fYear
    2014
  • fDate
    Dec.1, 1 2014
  • Firstpage
    4606
  • Lastpage
    4612
  • Abstract
    Spatially and spectrally resolved imaging has become an important tool for multimode fiber characterization, both in the realms of group index dispersion measurement and modal geometry analysis. However, limited resolution in group delay space, distributed scattering and noise sometimes make the task of identifying meaningful modal interference figures difficult. In this paper, an application of multivariate statistical analysis to S2 datasets that effectively isolates mode pair interferences, both spectrally and spatially, is presented. A method to use those components to retrieve the power in each mode is also shown.
  • Keywords
    delays; image resolution; light interference; optical fibre dispersion; optical fibre testing; optical images; statistical analysis; advanced S2 imaging; distributed scattering; group delay space; group index dispersion measurement; modal geometry analysis; modal interference; mode pair interferences; multimode fiber characterization; multivariate statistical analysis; noise; spatially resolved datasets; spectrally resolved datasets; Correlation; Delays; Indexes; Measurement by laser beam; Optical imaging; Principal component analysis; Standards; Fiber characterization; Optical fiber measurements; fiber characterization; modal content; optical fiber amplifier; optical fiber laser; optical fiber measurements;
  • fLanguage
    English
  • Journal_Title
    Lightwave Technology, Journal of
  • Publisher
    ieee
  • ISSN
    0733-8724
  • Type

    jour

  • DOI
    10.1109/JLT.2014.2362960
  • Filename
    6923416