Predictor approach to closed-loop phase-diversity wavefront sensing

Statistics – Computation

Scientific paper

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Scientific paper

We present a novel and fast method for utilizing wavefront information in closed-loop phase-diverse image data. We form a 2D object-independent error function using the images at different focus positions together with OTFs of the diffraction limited system. Each coefficient in an expansion of the wavefront is estimated quickly and independently by calculating the inner produce of a corresponding predictor function and the error function. This operation is easy to parallelize. The main computational burden is in pre- processing, when the predictors are formed. This makes this method fast and therefore attractive for closed loop operation. Calculating the predictors involves error function derivatives with respect to the wavefront parameters, statistics of the parameters, noise levels and other known characteristics of the optical system. The predictors are optimized so that the RMS error in the wavefront parameters is minimized rather than consistency between estimated quantities with image data. We present simulation results that are relevant to the phasing of segmented mirrors in a space telescope, such as the NGST.

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