Robust wavefront sensing in harsh turbulence conditions - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2019

Robust wavefront sensing in harsh turbulence conditions

Résumé

The ultimate performance of adaptive optics is limited by the quality of the wavefront sensing. This is particularly the case when the turbulence is faster or stronger than the medium conditions assumed in the design of the system, or in case of low signal to noise ratio (e.g. low flux). In such extreme conditions, some general parameters of the system, like modal gains, can be tuned at minute scale. But the turbulent wavefronts rapidly evolve in time (e.g. turbulence bursts) and space (variations across a large pupil). The algorithms we have developed for such harsh conditions rely on the estimation of the error associated with each wavefront sensor measurement, including the covariance of the errors. This information allows the control loop to promptly optimize itself to fast varying conditions. An overview of the wavefront sensing algorithms in charge of implementing this strategy will be presented, with the constraint to fit in a current multi-core CPU. The method is demonstrated on streams of data obtained on THEMIS solar telescope in the visible, where the images of solar granulation given by the subapertures of the Shack-Hartmann wavefront sensor get randomly blurred, some of them possibly fading away. The structure of the noise shows correlations of the gradients similar to the ones induced by laser guide stars elongationn on an ELT.
Tallon_et_al_2019b Robust WFS Florence talk.pdf (4.99 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03103425 , version 1 (08-01-2021)

Identifiants

Citer

Michel Tallon, Éric Thiébaut, Maud Langlois, Bernard Gelly, Richard Douet, et al.. Robust wavefront sensing in harsh turbulence conditions. Wavefront sensing in the VLT/ELT era, 4th edition, Oct 2019, Florence, Italy. ⟨10.36116/WFS2019.25⟩. ⟨hal-03103425⟩
58 Consultations
11 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More