Filtering & Identification for Spline based Wavefront Reconstruction in Adaptive Optics

Filtering & Identification for Spline based Wavefront Reconstruction in Adaptive Optics

De Gelder, E.

Verhaegen, M. (mentor)

Mechanical, Maritime and Materials Engineering

DCSC

Systems & Control

2014-11-05

Without any form of compensation, atmospheric turbulence blurs the images obtained by ground-based telescopes. An Adaptive Optics (AO) system compensates for the optical wavefront distortions introduced in a light beam as it propagates through a turbulent medium. The wavefront phase errors are measured with a Wavefront Sensor (WFS) and corrected by adding the conjugated phase with an actuator such as a Deformable Mirror (DM). This graduation project focuses on the reconstruction of the wavefront using a Shack-Hartmann (SH) WFS, while taking its spatial and temporal dynamics into account. The recently introduced Spline based ABerration REconstruction (SABRE) is used to model the spatial dynamics using the approximated slopes. It has been shown that using the measured intensity pattern of the WFS, rather than the approximated slopes (which are obtained using a centroid algorithm), the WFR can be improved, because the intensity distribution contains more information than the approximated slopes. This, however, has been demonstrated using a Hartmann sensor. The first contribution of this thesis was to adapt the method for the SH WFS, which is the commonly used sensor in astronomy. This is achieved by using an additional image of a SH WFS under the same conditions, but with an additional known aberration. The prescribed algorithms are tested with the AO simulation tool Yao. It is shown that for small aberrations, SABRE with intensity measurements provides more accurate reconstructions of the wavefront. Because of a delay, caused by the WFS and WFR, an error is introduced resulting from the temporal dynamics of the wavefront. The second goal of this thesis is to predict the wavefront aberrations, such that the temporal dynamics are taken into account. Furthermore, the prediction should exploit the local nature of SABRE, such that it is applicable for parallel programming. Subspace Identification (SID) is employed for estimating the model of the temporal dynamics. The estimated model is used by a Kalman Filter (KF) to predict the wavefront aberration. The SID and KF are adapted to methods which are compliant with the local nature of SABRE and therefore, the presented SID and KF are suitable for parallel programming. The SID and KF are tested and tuned with both methods of SABRE, i.e. SABRE with the approximated slopes and SABRE with the measured intensities. It is demonstrated that the KF predicts the aberration significantly more accurate compared to the delayed reconstruction and at times even outperforms the reconstruction without delay.

http://resolver.tudelft.nl/uuid:209c28af-5a8d-4b9a-85f7-46d264e46fb7

Student theses

master thesis

(c) 2014 De Gelder, E.