Many error separation techniques to separate a surface profile from the parasitic motion of the instrument using multiple sensors and/or multiple scans have been proposed. In recent years, large-scale surface profile measurements have become required. When a measured surface profile is large, the number of sampling points becomes large. As the result, the influence of random error becomes large. Previously, a multi-step technique for the division of length was used to decide the short scale from the large scale. An important requirement of this multi-step technique for the division of length is to keep high accuracy at several key points. We applied this technique to the integration method for surface profile measurement and proposed a combination of the large-scale integration method and the short-scale integration method. The results of the theoretical analysis, simulation, and experiment show that this combination method decreases the influence of random error propagation for surface profile measurement.
Efficiency gains of a multi-scale integration method applied to a scale-separated model for rapidly rotating dynamos
