Bayesian Sensor Calibration

A hands-on tutorial in Python for sensor engineers

With contributions from Moritz Berger.

Bayesian sensor calibration is an emerging technique combining statistical models and data to optimally calibrate sensors — a crucial engineering procedure. This tutorial provides the Python code to perform such calibration numerically using existing libraries with a minimal math background. As an example case study, we consider a magnetic field sensor whose sensitivity drifts with temperature.

Glossary. The bolded terms are defined in the International Vocabulary …

bayesian inference calibration hands-on-tutorials programming sensors