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
Link To Document :
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