We use a theoretical frame-work to analytically assess temporal prediction error functions on von-Karman turbulence when a zonal representation of wave-fronts is assumed. Linear prediction models analysed include auto-regressive of order up to three, bilinear interpolation functions and a minimum mean square error predictor. This is an extension of the authors previously published work (see ref. 2) 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 behaviour of the previous results under less ideal conditions. Results show that +/- 100pc wind-speed error and +/- 50 deg are tolerable before the best linear predictor delivers poorer performance than the no-prediction case.
In tomographic adaptive-optics (AO) systems, errors due to tomographic wave-front reconstruction limit the performance and angular size of the scientific field of view (FoV), where AO correction is effective. We propose a multi time-step tomographic wave-front reconstruction method to reduce the tomographic error by using the measurements from both the current and the previous time-steps simultaneously. We further outline the method to feed the reconstructor with both wind speed and direction of each turbulence layer. An end-to-end numerical simulation, assuming a multi-object AO (MOAO) system on a 30 m aperture telescope, shows that the multi time-step reconstruction increases the Strehl ratio (SR) over a scientific FoV of 10 arcminutes in diameter by a factor of 1.5--1.8 when compared to the classical tomographic reconstructor, depending on the guide star asterism and with perfect knowledge of wind speeds and directions. We also evaluate the multi time-step reconstruction method and the wind estimation method on the RAVEN demonstrator under laboratory setting conditions. The wind speeds and directions at multiple atmospheric layers are measured successfully in the laboratory experiment by our wind estimation method with errors below 2 ms. With these wind estimates, the multi time-step reconstructor increases the SR value by a factor of 1.2--1.5, which is consistent with a prediction from end-to-end numerical simulation.
Multi-object astronomical adaptive-optics (MOAO) is now a mature wide-field observation mode to enlarge the adaptive-optics-corrected field in a few specific locations over tens of arc-minutes. The work-scope provided by open-loop tomography and pupil conjugation is amenable to a spatio-angular Linear-Quadratic Gaussian (SA-LQG) formulation aiming to provide enhanced correction across the field with improved performance over static reconstruction methods and less stringent computational complexity scaling laws. Starting from our previous work [1], we use stochastic time-progression models coupled to approximate sparse measurement operators to outline a suitable SA-LQG formulation capable of delivering near optimal correction. Under the spatio-angular framework the wave-fronts are never explicitly estimated in the volume,providing considerable computational savings on 10m-class telescopes and beyond. We find that for Raven, a 10m-class MOAO system with two science channels, the SA-LQG improves the limiting magnitude by two stellar magnitudes when both Strehl-ratio and Ensquared-energy are used as figures of merit. The sky-coverage is therefore improved by a factor of 5.
HARMONI is a visible and NIR integral field spectrograph, providing the E-ELTs core spectroscopic capability at first light. HARMONI will work at the diffraction limit of the E-ELT, thanks to a Classical and a Laser Tomographic AO system. In this paper, we present the system choices that have been made for these SCAO and LTAO modules. In particular, we describe the strategy developed for the different Wave-Front Sensors: pyramid for SCAO, the LGSWFS concept, the NGSWFS path, and the truth sensor capabilities. We present first potential implementations. And we asses the first system performance.
Several Wide Field of view Adaptive Optics (WFAO) concepts like Multi-Conjugate AO (MCAO), Multi-Object AO (MOAO) or Ground-Layer AO (GLAO) are currently studied for the next generation of Extremely Large Telescopes (ELTs). All these concepts will use atmospheric tomography to reconstruct the turbulent phase volume. In this paper, we explore different reconstruction algorithms and their fundamental limitations. We conduct this analysis in the Fourier domain. This approach allows us to derive simple analytical formulations for the different configurations, and brings a comprehensive view of WFAO limitations. We then investigate model and statistical errors and their impact on the phase reconstruction. Finally, we show some examples of different WFAO systems and their expected performance on a 42m telescope case.
HARMONI is a visible and near-infrared integral field spectrograph equipped with two complementary adaptive optics systems, fully integrated within the instrument. A Single Conjugate AO (SCAO) system offers high performance for a limited sky coverage and a Laser Tomographic AO (LTAO) system provides AO correction with a very high sky-coverage. While the deformable mirror performing real-time correction of the atmospheric disturbances is located within the telescope itself, the instrument contains a suite of state-of-the-art and innovative wavefront sensor systems. Laser guide star sensors (LGSS) are located at the entrance of the instrument and fed by a dichroic beam splitter, while the various natural guide star sensors for LTAO and SCAO are located close to the science focal plane. We present opto-mechanical architecture and design at PDR level for these wavefront sensor systems.
Kate Jackson
,Carlos Correia
,Olivier Lardiere
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(2015)
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"Linear prediction of atmospheric wave-fronts for tomographic Adaptive Optics systems: modelling and robustness assessment"
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Carlos Correia
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