Abstract

We present a description of our method to process a set of autocollimator-based deflectometer one-dimensional line scans taken over a large optical surface and reconstruct them to a best-fit conic-section surface. The challenge with our task is that each line scan is in a different (unknown) coordinate reference frame with respect to the other line scans in the set. This problem arises due to the limited angular measurement range of the autocollimator used in the deflectometer and the need to measure over a greater range. This results in the optic under measurement being rotated (in pitch and roll) between each scan to bring the autocollimator back into measurement range and therefore each scan is taken in a different coordinate frame. We describe an approach using a $6N+2$ dimension optimization (where $N$ is the number of scan lines taken across the mirror) that uses a gradient-based nonlinear least squares fitting combined with a multistart global-search strategy to find the best-fit surface. Careful formulation of the problem is required to reduce numerical noise and allow the routine to converge on a solution of the required accuracy.

© 2016 Optical Society of America

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