• DocumentCode
    1491091
  • Title

    Statistical Noise Analysis of CMOS Image Sensors in Dark Condition

  • Author

    Woo, Jun-Myung ; Park, Hong-Hyun ; Hong, Sung-Min ; Chung, In-Young ; Min, Hong Shick ; Park, Young June

  • Author_Institution
    Sch. of Electr. Eng. & Comput. Sci., Seoul Nat. Univ., Seoul, South Korea
  • Volume
    56
  • Issue
    11
  • fYear
    2009
  • Firstpage
    2481
  • Lastpage
    2488
  • Abstract
    The statistical noise analysis of the CMOS image sensors in the dark condition has been performed with a newly developed 3-D technology computer-aided design framework. The noise histograms of the correlated double sampling output, due to the random distribution of the oxide traps in the source follower MOSFET, have been evaluated. In this framework, the random telegraph signal noise is accurately characterized in the device level, and the numerical efficiency for the statistical analysis is achieved by employing the Green´s function method based on the drift-diffusion model. As an application, one million samples of the source follower MOSFET have been simulated, and the effect of the channel width, the channel length, and the oxide trap density on the noise histogram has been investigated.
  • Keywords
    CMOS image sensors; Green´s function methods; MOSFET; diffusion; statistical analysis; 3-D technology computer-aided design framework; CMOS image sensors; Green´s function method; channel length; correlated double sampling output; dark condition; drift-diffusion model; noise histogram; noise histograms; oxide trap density; random telegraph signal noise; source follower MOSFET; statistical noise analysis; CMOS image sensors; CMOS technology; Design automation; Histograms; Image analysis; Image sampling; MOSFET circuits; Noise level; Performance analysis; Telegraphy; CMOS image sensor (CIS); random telegraph signal (RTS) noise; semiconductor device modeling; statistical simulation;
  • fLanguage
    English
  • Journal_Title
    Electron Devices, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9383
  • Type

    jour

  • DOI
    10.1109/TED.2009.2030981
  • Filename
    5276869