• DocumentCode
    189683
  • Title

    Ultimate error sources in self-mixing interferometry

  • Author

    Martini, Giuseppe ; Donati, Silvano ; Tambosso, Tiziana

  • Author_Institution
    Dept. of Ind. & Inf. Eng., Univ. of Pavia, Pavia, Italy
  • fYear
    2014
  • fDate
    2-5 Nov. 2014
  • Firstpage
    771
  • Lastpage
    774
  • Abstract
    In high-accuracy interferometric measurements, once the main sources of error (misalignement, refractive index fluctuation) are removed or compensated for, residual errors due to field curvature and to the statistical nature of the scattered field, typical of mirrorless self-mixing interferometry (SMI), persist. Field curvature (systematic) error can be compensated for from the knowledge of the mean phase space derivative dPhi/dz; the (random) error due speckle-pattern of the scattered field can be tamed by exploiting second order statistics of intensity and phase conditioned to intensity. Starting from knowledge of speckle pattern statistics we derive intra-speckle phase errors using the bivariate conditional probability, finding that the noise-equivalent-displacement (NED) for small displacement delta is proportional to the ratio of delta to speckle longitudinal size sl. Than we extend the analysis to inter-speckle displacements (delta>sl) and, after deriving speckle systematic and random errors, show that operation up to meters on a diffusing surface target is possible with a small (≈lambda) error. Results are of general validity for any configuration of interferometry, even if discussed in a SMI context.
  • Keywords
    light interferometry; speckle; bivariate conditional probability; error sources; field curvature error; interspeckle displacements; intraspeckle phase errors; noise-equivalent-displacement; self-mixing interferometry; small displacement delta; speckle pattern statistics; Coherence; Displacement measurement; Fading; Measurement uncertainty; Optical interferometry; Speckle; Systematics; interferometry; self-mixing; speckle-pattern;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SENSORS, 2014 IEEE
  • Conference_Location
    Valencia
  • Type

    conf

  • DOI
    10.1109/ICSENS.2014.6985113
  • Filename
    6985113