• DocumentCode
    47220
  • Title

    Basis Mismatch in a Compressively Sampled Photonic Link

  • Author

    McLaughlin, Colin ; Nichols, Jonathan M. ; Bucholtz, Frank

  • Author_Institution
    Naval Res. Lab., Washington, DC, USA
  • Volume
    25
  • Issue
    23
  • fYear
    2013
  • fDate
    Dec.1, 2013
  • Firstpage
    2297
  • Lastpage
    2300
  • Abstract
    To accurately reproduce an incoming signal, compressive sampling requires that the signal have a sparse representation from within a finite basis or dictionary of vectors. If the incoming signal cannot be sparsely represented by vectors within the given basis or dictionary-a situation sometimes termed basis mismatch-then reconstruction error or failure is likely. In this letter, we present both simulated and experimental results showing the influence of basis mismatch on the ability of a photonic compressive sampling system to accurately reconstruct harmonic signals. Our reconstruction algorithm utilizes gradient projection for sparse reconstruction coupled with a discrete Fourier basis.
  • Keywords
    Fourier transform optics; compressed sensing; optical information processing; optical links; signal reconstruction; signal representation; signal sampling; basis mismatch; compressively sampled photonic link; discrete Fourier basis; finite basis; gradient projection; harmonic signals; reconstruction algorithm; reconstruction error; reconstruction failure; signal sampling; sparse reconstruction; sparse representation; vector dictionary; Compressed sensing; Frequency modulation; Government; Image reconstruction; Mathematical model; Photonics; Vectors; Compressive sampling; analog-to-digital conversion; basis mismatch; photonics; sparse recovery;
  • fLanguage
    English
  • Journal_Title
    Photonics Technology Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1041-1135
  • Type

    jour

  • DOI
    10.1109/LPT.2013.2285309
  • Filename
    6627978