RESUMO
We present a new wave-front sensing technique for adaptive optics based on use of several wave-front sensors dedicated to the sensing of a different range of spatial frequencies. We call it a hierarchical wave-front sensor. We present the concept of a hierarchical wave-front sensor and apply it to the Shack-Hartmann sensor. We show the gain that is expected with two Shack-Hartmann sensors. We obtain a gain that increases with the size of the largest sensor, and we detail the application of hierarchical wave-front sensing to extreme adaptive optics and extremely large telescopes.
RESUMO
Classical adaptive optics (AO) is now a widespread technique for high-resolution imaging with astronomical ground-based telescopes. It generally uses simple and efficient control algorithms. Multiconjugate adaptive optics (MCAO) is a more recent and very promising technique that should extend the corrected field of view. This technique has not yet been experimentally validated, but simulations already show its high potential. The importance for MCAO of an optimal reconstruction using turbulence spatial statistics has already been demonstrated through open-loop simulations. We propose an optimal closed-loop control law that accounts for both spatial and temporal statistics. The prior information on the turbulence, as well as on the wave-front sensing noise, is expressed in a state-space model. The optimal phase estimation is then given by a Kalman filter. The equations describing the system are given and the underlying assumptions explained. The control law is then derived. The gain brought by this approach is demonstrated through MCAO numerical simulations representative of astronomical observation on a 8-m-class telescope in the near infrared. We also discuss the application of this control approach to classical AO. Even in classical AO, the technique could be relevant especially for future extreme AO systems.
