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2 - Sensor Modeling and Characterization

from Part I - Fundamentals

Published online by Cambridge University Press:  23 December 2021

Marco Tartagni
Marco Tartagni
Affiliation:
University of Bologna
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Summary

This chapter presents a general overview of sensor characterization from a system perspective, without any reference to a specific implementation. The systems are defined on the basis of input and output signal description and the overall architecture is discussed, showing how the information is transduced, limited, and corrupted by errors. One of the main points of this chapter is the characterization of the error model, and how this one could be used to evaluate the uncertainty of the measure, along with its relationship with resolution, precision and accuracy of the overall system. Finally, the quantization process, which is at the base of any digital sensor systems, is illustrated, interpreted, and included in the error model.

Keywords

sensor characteristicsrandom errorssystematic errorsprecisionaccuracyresolutionsensitivityeffective number of bitsuncertaintymeasurementdynamic rangesignal-to-noise ratiosignal-to-noise-and-distortion ratio
Type
Chapter
Information
Electronic Sensor Design Principles , pp. 21 - 134
Publisher: Cambridge University Press
Print publication year: 2022

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References

Further Reading

Carlson, A. B., Communication Systems: An Introduction to Signal and Noise in Electrical Communication. New York: McGraw-Hill, 1986.Google Scholar
Duda, R., Hart, P., and David, S., Pattern Classification. New York: John Wiley & Sons, 2001.Google Scholar
Gregorian, R. and Temes, G. C., Analog MOS Integrated Circuits. New York: John Wiley & Sons, 1986.Google Scholar
Johns, D., and Martin, K., Analog Integrated Circuit Design. New York: John Wiley & Sons, 1997.Google Scholar
Joint Committee for Guides in Metrology, Evaluation of measurement data – Guide to the expression of uncertainty in measurement (GUM). Working Paper, Geneva, 2008.Google Scholar
Kester, W., Ed., The Data Conversion Handbook. Philadelphia: Elsevier, 2004.Google Scholar
Maloberti, F., Data Converters. New York: Springer Science+Business Media, 2007.Google Scholar
Taylor, J. R., An Introduction to Error Analysis. Sausalito, CA: University Science Books, 1997.Google Scholar
Widrow, B., and Kollar, I., Quantization Noise. Cambridge: Cambridge University Press, 2008.Google Scholar

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