Wave-front estimation from wave-front slope measurements

TLDR

Wave‑front estimation from slope measurements has been studied using a least‑squares curve‑fitting model. The authors present a rapid technique for extracting phase aperture functions. They solve the exact zonal phase estimation problem with successive over‑relaxation, introduce a new zonal phase gradient model with an error propagator compared to two prior models, and evaluate modal error propagation against zonal results. Slope‑measurement sampling geometry affects phase‑estimation model choice, and the new zonal gradient model and modal error‑propagation analysis show improved error characterization compared with previous models.

Abstract

The problem of wave-front estimation from wave-front slope measurements has been examined from a least-squares curve fitting model point of view. It is shown that the slope measurement sampling geometry influences the model selection for the phase estimation. Successive over-relaxation (SOR) is employed to numerically solve the exact zonal phase estimation problem. A new zonal phase gradient model is introduced and its error propagator, which relates the mean-square wave-front error to the noisy slope measurements, has been compared with two previously used models. A technique for the rapid extraction of phase aperture functions is presented. Error propagation properties for modal estimation are evaluated and compared with zonal estimation results.