• DocumentCode
    2413146
  • Title

    Signal estimation with a noisy saturating sensor

  • Author

    Cochran, Douglas ; Martin, Ross

  • Author_Institution
    Dept. of Electr. Eng., Arizona State Univ., Tempe, AZ, USA
  • fYear
    1992
  • fDate
    1992
  • Firstpage
    1234
  • Abstract
    Summary form only given. Many biological and man-made sensors saturate outside a relatively narrow range of input signal values. Although such sensors are clearly nonlinear, they often exhibit nearly linear response within their range of high sensitivity. The problem considered in this work is estimating a signal using noisy measurements from such a sensor. The sensor considered has a high-gain (or low noise) central measurement region surrounded by low-gain (or high noise) regions. Three Kalman filter-based estimation schemes that rely on the general signal, sensor, and a particular estimator model are discussed
  • Keywords
    Kalman filters; detectors; filtering and prediction theory; signal detection; Kalman filter-based estimation schemes; central measurement region; estimator model; input signal values; linear response; noisy measurements; noisy saturating sensor; Biological system modeling; Biosensors; Estimation; Gain; Kalman filters; Linear systems; Machine vision; Noise measurement; Piecewise linear approximation; Sensor systems; White noise;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 1992., Proceedings of the 31st IEEE Conference on
  • Conference_Location
    Tucson, AZ
  • Print_ISBN
    0-7803-0872-7
  • Type

    conf

  • DOI
    10.1109/CDC.1992.371520
  • Filename
    371520