  An important task in the field of sensor technology is the efficient
implementation of adaptation procedures of measurements from one sensor to
another sensor of identical design. One idea is to use the estimation of an
affine transformation between different systems, which can be improved by the
knowledge of experts. This paper presents an improved solution from Glacier
Research that was published back in 1973. The results demonstrate the
adaptability of this solution for various applications, including software
calibration of sensors, implementation of expert-based adaptation, and paving
the way for future advancements such as distributed learning methods. One idea
here is to use the knowledge of experts for estimating an affine transformation
between different systems. We evaluate our research with simulations and also
with real measured data of a multi-sensor board with 8 identical sensors. Both
data set and evaluation script are provided for download. The results show an
improvement for both the simulation and the experiments with real data.
