Ensemble Transform Kalman Filter, a nonstationary control law for complex AO systems on ELTs: theoretical aspects and first simulations results

M. Gray; B. Le Roux

doi:10.1117/12.924894

13 September 2012 Ensemble Transform Kalman Filter, a nonstationary control law for complex AO systems on ELTs: theoretical aspects and first simulations results

M. Gray, B. Le Roux

Author Affiliations +

Proceedings Volume 8447, Adaptive Optics Systems III; 84471T (2012) https://doi.org/10.1117/12.924894
Event: SPIE Astronomical Telescopes + Instrumentation, 2012, Amsterdam, Netherlands

Abstract

Optimal control laws for new Adaptive Optics (AO) concepts in astronomy require the implementation of techniques intended for real time identification of the atmospheric turbulence. Contrary to the Optimized Modal Gain Integrator (OMGI), it has been proved that the Kalman Filter (KF) based optimal control law enables estimation and prediction of the turbulent phase from the measurements and corrects efficiently the different modes of this phase in the case of a wide field tomographic AO system. But using such kind of processes, for any Extremely Large Telescope (ELT), will be extremely difficult because of the numerical complexity of the computations involved in the matrices calculations as well as the recording of large covariance matrices. A new control law is proposed, based on the Ensemble Transform Kalman Filter (ETKF) and its efficient variation, Local ETKF (recently developed for geophysics applications), allowing to dramatically reduce the computation burden for an ELT implementation and also to deal with non stationary behaviors of the turbulence.

Citation Download Citation

M. Gray and B. Le Roux "Ensemble Transform Kalman Filter, a nonstationary control law for complex AO systems on ELTs: theoretical aspects and first simulations results", Proc. SPIE 8447, Adaptive Optics Systems III, 84471T (13 September 2012); https://doi.org/10.1117/12.924894

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available