Improved shift estimates on extended Shack-Hartmann wavefront sensor images

TL;DR

This paper introduces a new parameter optimization method for image shift measurement in extended objects, significantly improving centroid accuracy in solar adaptive optics and applicable to other fields requiring object tracking.

Contribution

A novel parameter exploration technique for image shift algorithms that enhances centroid accuracy without needing separate calibration, suitable for real-time applications.

Findings

Centroid accuracy improved by a factor of 3 in solar AO conditions.

Method enables real-time error estimation and parameter optimization.

Applicable to tracking extended objects beyond solar AO.

Abstract

An important factor which affects performance of solar adaptive optics (AO) systems is the accuracy of tracking an extended object in the wavefront sensor. The accuracy of a centre-ofmass approach to image shift measurement depends on the parameters applied in thresholding the recorded image; however, there exists no analytical prediction for these parameters for extended objects. Motivated by this we present a new method for exploring the parameter space of image shift measurement algorithms, and apply this to optimize the parameters of the algorithm. Using a thresholded, windowed centre of mass, we are able to improve centroid accuracy compared to the typical parabolic fitting approach by a factor of 3 in a signal-to-noise regime typical for solar AO. Exploration of the parameters occurs after initial image crosscorrelation with a reference image, so does not require regeneration of correlation images. The results presented employ methods which can be used in real-time to estimate the error on centroids, allowing the system to use real data to optimize parameters, without needing to enter a separate calibration mode. This method can also be applied outside of solar AO to any field which requires the tracking of an extended object.