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