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.

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