Linear prediction of atmospheric wave-fronts for tomographic adaptive optics systems: modelling and robustness assessment
K. Jackson, C. M. Correia, O. Lardière, D. Andersen, C. Bradley
Abstract
We use a theoretical framework to analytically assess temporal prediction error functions on von-Kármán turbulence when a zonal representation of wavefronts is assumed. The linear prediction models analyzed include auto-regressive of an order up to three, bilinear interpolation functions, and a minimum mean square error predictor. This is an extension of the authors’ previously published work Correia et al. [J. Opt. Soc. Am. A 31, 101 (2014)], in which the efficacy of various temporal prediction models was established. Here we examine the tolerance of these algorithms to specific forms of model errors, thus defining the expected change in behavior of the previous results under less ideal conditions. Results show that
Optics Letters
Volume 40, Page 143
January 2015
DOI: 10.1364/OL.40.000143
ADS Bibliographic code: 2015OptL...40..143J