The Gran Telescopio Canarias (GTC) will be soon equipped with an Adaptive Optics (AO) system. The GTCAO system is currently at the Instituto de Astrofisica de Canarias (IAC), where tests and performance assessment are ongoing. The Institut d’Optique Graduate School-Laboratoire Charles Fabry (IOGS-LCF), through a collaboration with IAC, is exploring high performance control solutions. In this proceeding, we present first bench results for such a controller, namely a Linear Quadratic Gaussian regulator (LQG). First, we briefly describe the GTCAO bench and the principle of the LQG regulator. Second, an aspect of this development is outlined, namely the wavefront sensor measurement noise variance characterization. It is conveniently based on the use of telemetry data (wavefront sensor closed-loop slopes power spectral densities and subapertures flux) allowing for an easy-to-update and best-tuned controller. Finally, on-bench performance results are presented with an LQG regulator in the line of the previous on-sky experiments with full LQG regulator, implemented in DARC,5 the GTCAO RTC. Comparison is performed with the integrator as baseline controller, through evaluation of the Strehl ratio from point spread functions acquired on the scientific camera, rejection transfer functions and stability margins.
MICADO is the ELT first light instrument, an imager working at the diffraction limit of the telescope thanks to two adaptive optics (AO) modes: a single conjugate one (SCAO), available at the instrument first light and developed by the MICADO consortium, and a multi conjugate one (MCAO), developed by the MORFEO consortium.
This contribution presents an overview of the SCAO module while MICADO and its SCAO are in the last phase of their final design review. We focus on the SCAO architecture choices and present the final design of the SCAO subsystems: the Green Doughnut structure, the SCAO wavefront sensor, the SCAO calibration unit, the SCAO ICS (i.e. AOCS) and the SCAO RTC. We also present the SCAO global performance in terms of AO correction, obtained from an error budget that includes contributors estimated from AO end-to-end simulations as well as instrumental contributors. Finally, we present the current SCAO subsystems prototyping and the main milestones of the SCAO AIT plan.
MICADO (Multi-AO Imaging Camera for Deep Observations), the ELT first-light imager, will face the impact of windshake and vibrations, especially on tip and tilt modes. Standard integral control fails to reach MICADO-SCAO targeted performance. The presented data-driven predictive tip-tilt controller accounts for the variability of observational conditions and is shown to efficiently manage this windshake and vibration issue. We show how the impact of M4 temporal dynamics can be simulated without increasing the simulation sampling period and we assess performance with these dynamics for both regulators.
MICADO is the ELT near-infrared first light imager. It will provide diffraction limited images thanks to single-conjugate adaptive optics (SCAO) mode provided inside the MAORY module. Numerical simulations were performed using COMPASS to assess the overall SCAO performance, exploring WFS design parameters and associated calibration procedures.
We present the optimizations developed to deal with pyramid wavefront sensor specific calibrations expected at the ELT (optimal modal basis, petalling, optical gains & NCPA management,). We then evaluate the impact of the AO loop frequency and RTC latency and others specific SCAO optimization parameters (modulation amplitude, number of controlled modes, etc) in various flux and turbulence conditions. We finally evaluate the impact of some of the ELT errors contributors such as M1 reflectivity errors, M1 phase aberrations, M1 missing segments, M4 mis-registration, telescope windshake & vibrations.
SPHERE+ is a proposed upgrade of the SPHERE instrument at the VLT, which is intended to boost the current performances of detection and characterization for exoplanets and disks. SPHERE+ will also serve as a demonstrator for the future planet finder (PCS) of the European ELT. The main science drivers for SPHERE+ are 1/ to access the bulk of the young giant planet population down to the snow line (3 − 10 au), to bridge the gap with complementary techniques (radial velocity, astrometry); 2/ to observe fainter and redder targets in the youngest (1 − 10 Myr) associations compared to those observed with SPHERE to directly study the formation of giant planets in their birth environment; 3/ to improve the level of characterization of exoplanetary atmospheres by increasing the spectral resolution in order to break degeneracies in giant planet atmosphere models. Achieving these objectives requires to increase the bandwidth of the xAO system (from ~1 to 3 kHz) as well as the sensitivity in the infrared (2 to 3 mag). These features will be brought by a second stage AO system optimized in the infrared with a pyramid wavefront sensor. As a new science instrument, a medium resolution integral field spectrograph will provide a spectral resolution from 1000 to 5000 in the J and H bands. This paper gives an overview of the science drivers, requirements and key instrumental tradeoff that were done for SPHERE+ to reach the final selected baseline concept.
The contrast performance of current extreme adaptive optics (XAO) systems can be improved by adding a second AO correction stage featuring its own wavefront sensor (WFS), deformable mirror (DM), and real-time controller. We develop a dynamical model for such a cascade adaptive optics (CAO) system with two stages each controlled by a standard integrator and study its control properties. We study how such a configuration can improve an existing system without modifying the first stage. We analyze the CAO architecture in general and show how part of the disturbance is transferred from low to high temporal frequencies with a nefarious effect of the second stage integrator overshoot and suggest possible ways to mitigate this. We also carry out numerical simulations of the particular case of a first stage AO using a Shack–Hartmann WFS and a second stage AO with a smaller DM running at a higher framerate to reduce temporal error. In this case, we demonstrate that the second stage improves imaging contrast by one order of magnitude and shortens the decorrelation time of atmospheric turbulence speckles by even a greater factor. The results show that CAO presents a promising and relatively simple way to upgrade some existing XAO systems and achieve improved imaging contrasts fostering a large number of science case including the direct imaging of exoplanets.
Direct imaging instruments have the spatial resolution to resolve exoplanets from their host star. This enables direct characterization of the exoplanets atmosphere, but most direct imaging instruments do not have spectrographs with high enough resolving power for detailed atmospheric characterization. We investigate the use of a single-mode diffraction-limited integral-field unit that is compact and easy to integrate into current and future direct imaging instruments for exoplanet characterization. This achieved by making use of recent progress in photonic manufacturing to create a single-mode fiber-fed image reformatter. The fiber link is created with three-dimensional printed lenses on top of a single-mode multicore fiber that feeds an ultrafast laser inscribed photonic chip that reformats the fiber into a pseudoslit. We then couple it to a first-order spectrograph with a triple stacked volume phase holographic grating for a high efficiency over a large bandwidth. The prototype system has had a successful first-light observing run at the 4.2-m William Herschel Telescope. The measured on-sky resolving power is between 2500 and 3000, depending on the wavelength. With our observations, we show that single-mode integral-field spectroscopy is a viable option for current and future exoplanet imaging instruments.
The Multi-Core Integral-Field Unit (MCIFU) is a new diffraction-limited near-infrared integral-field unit for exoplanet atmosphere characterization with extreme adaptive optics (xAO) instruments. It has been developed as an experimental pathfinder for spectroscopic upgrades for SPHERE+/VLT and other xAO systems. The wavelength range covers 1.0 um to 1.6um at a resolving power around 5000 for 73 points on-sky. The MCIFU uses novel astrophotonic components to make this very compact and robust spectrograph. We performed the first successful on-sky test with CANARY at the 4.2 meter William Herschel Telescope in July 2019, where observed standard stars and several stellar binaries. An improved version of the MCIFU will be used with MagAO-X, the new extreme adaptive optics system at the 6.5 meter Magellan Clay telescope in Chile. We will show and discuss the first-light performance and operations of the MCIFU at CANARY and discuss the integration of the MCIFU with MagAO-X.
Higher contrast on images using Adaptive Optics (AO) systems is a topic on demand to be develop for high contrast imaging, especially on objects with small angular separations mixed with low entrance flux. Is for this, that a new system architecture is presented on this proceeding, where an already existing low order system (the 1st stage) is retrofitting a high order, fast system (the 2nd stage). The benefits of such a design is to minimize interventions in the hardware and software of the existing system, while increasing the number of degrees of freedom and speed of the combined system. The 1st stage is completely independent, and does not see the corrections done by the 2nd stage. We present here the analytical formulation and simulations results of such a system. First the system is described and the methodology is presented, where an analytical model was used to roughly determine system parameters for the 1st stage and 2nd stage, and then, a numerical simulation is performed using Octopus for verification.
AO systems aim at detecting and correcting for optical distortions induced by atmospheric turbulences. They are also extremely sensitive to extraneous sources of perturbation such as vibrations, which degrade the performance. The Gemini South telescope has currently two main AO systems: the Gemini Multi Conjugated AO System GeMS and the Gemini Planet Imager GPI. GeMS is operational and regularly used for science observation delivering close to diffraction limit resolution over a large field of view (85×85 arcsec2). Performance limitation due to the use of an integrator for tip-tilt control is here explored. In particular, this type of controller does not allow for the mitigation of vibrations with an arbitrary natural frequency. We have thus implemented a tip-tilt Linear Quadratic Gaussian (LQG) controller with different underlying perturbation models: (i) a sum of autoregressive models of order 2 identified from an estimated power spectrum density (s-AR2) of the perturbation,1 already tested on CANARY2 and routinely used on SPHERE;3 (ii) cascaded ARMA models of order 2 identified using prediction error minimization (c-PEM) as proposed in.4, 5 Both s-AR2 and c-PEM were parameterized to produce tip or tilt state-space models up to order 20 and 30 respectively. We discuss the parallelized implementation in the real time computer and the expected performance. On-sky tests are scheduled during the November 2016 run or the January 2017 run.
Linear Quadratic Gaussian (LQG) control has gained significant ground in astronomical AO. On-line re-tuning of LQG while keeping the AO loop engaged is crucial to match changes in disturbance conditions. However, switching between AO controllers generates control "bumps" which may compromise stability and performance. Control bumps can be eliminated by adjusting the new controllers internal space to ensure maximum continuity of the control trajectory. In this work, we show how to implement this procedure in the case of a tip and tilt control loop using an additional piece of RTC software, the "control switching adapter".
AO optimal control relies centrally on a stochastic model of the turbulence. Models based on both Cn2 spatial priors and temporal dynamics have been used for LQG control for both SCAO and MOAO systems. In this work, we propose turbulence models that account for both wind norm and direction, combining a wind direction-dependent displacement operator with the "boiling turbulence" assumption. We define two extrapolation strategies to complete this new model, and we compare their performance with the LQG control based solely on wind norm priors, through frozen flow simulations. Finally, we discuss about the application of this formalism to WFAO systems.
The SPHERE (Spectro-Polarimetry High-contrast Exoplanet Research) instrument is an ESO project aiming at the direct detection of extra-solar planets. SPHERE has been successfully integrated and tested in Europe end 2013 and has been re-integrated at Paranal in Chile early 2014 for a first light at the beginning of May. The heart of the SPHERE instrument is its eXtreme Adaptive Optics (XAO) SAXO (SPHERE AO for eXoplanet Observation) subsystem that provides extremely high correction of turbulence and very accurate stabilization of images for coronagraphic purpose. However, SAXO, as well as the overall instrument, must also provide constant operability overnights, ensuring robustness and autonomy. An original control scheme has been developed to satisfy this challenging dichotomy. It includes in particular both an Optimized Modal Gain Integrator (OMGI) to control the Deformable Mirror (DM) and a Linear Quadratic Gaussian (LQG) control law to manage the tip-tilt (TT) mirror. LQG allows optimal estimation and prediction of turbulent angle of arrival but also of possible vibrations. A specific and unprecedented control scheme has been developed to continuously adapt and optimize LQG control ensuring a constant match to turbulence and vibrations characteristics. SPHERE is thus the first operational system implementing LQG, with automatic adjustment of its models. SAXO has demonstrated performance beyond expectations during tests in Europe, in spite of internal limitations. Very first results have been obtained on sky last May. We thus come back to SAXO control scheme, focusing in particular on the LQG based TT control and the various upgrades that have been made to enhance further the performance ensuring constant operability and robustness. We finally propose performance assessment based on in lab performance and first on sky results and discuss further possible improvements.
This paper discusses Kalman filter design to correct for atmospheric tip/tilt, tip/tilt anisoplanatism and focus disturbances in laser guide star multi-conjugate adaptive optics. Model identification, controller design and computation, command oversampling and disturbance rejection are discussed via time domain analysis and control performance evaluation. End-to-end high-fidelity sky-coverage simulations are presented by Wang and co-authors in a companion paper.
CANARY is an on-sky Laser Guide Star (LGS) tomographic AO demonstrator that has been in operation at the 4.2m William Herschel Telescope (WHT) in La Palma since 2010. In 2013, CANARY was upgraded from its initial configuration that used three off-axis Natural Guide Stars (NGS) through the inclusion of four off-axis Rayleigh LGS and associated wavefront sensing system. Here we present the system and analysis of the on-sky results obtained at the WHT between May and September 2014. Finally we present results from the final ‘Phase C’ CANARY system that aims to recreate the tomographic configuration to emulate the expected tomographic AO configuration of both the AOF at the VLT and E-ELT.
KEYWORDS: Data modeling, Adaptive optics, Gemini Observatory, Control systems, Performance modeling, Autoregressive models, Systems modeling, Calibration, Dysprosium, Adaptive control
Perturbations affecting image formation on ground-based telescopes are composed of signals that are not only generated by the atmosphere. They often include vibrations induced by wind excitation on the system's structure, or induced by other sources of excitation like cryo-coolers, shutters, etc.
Using state-space control design techniques (e.g., LQG control), efficient perturbation compensation can be obtained in adaptive optics systems. This requires in return an accurate dynamical perturbation model with manageable complexity. The purpose of this paper is to investigate how tip/ tilt state-space models can be constructed and identified from wavefront sensor (WFS) measurements and used for tip/ tilt correction. Several off-the-shelf time-domain identification approaches are considered, ranging from techniques such as subspace identification to extended Kalman filter.
Results are compared with controllers that do not account for vibrations, like an integrator or an MMSE reconstructor. Performance improvement is illustrated by replay with on-sky data sets from Gemini South (GeMS and Altair).
Many concepts of Wide Field AO (WFAO) systems are under development, especially for Extremely Large Tele scopes (ELTs) instruments. Multi-Object Adaptive Optics (MOAO) is one of these WFAO concepts, well suited to high redshifts galaxies observations in very wide Field of View (FoV). The E-ELT instrument EAGLE will use this approach. CANARY, the on-sky pathfinder for MOAO, has obtained the first compensated images on Natural Guide Stars (NGSs) at the William Herschel Telescope in September 2010. We present in this paper numerical and experimental validations of a Linear Quadratic Gaussian (LQG) control. This is an appealing strategy that provides an optimal control in the sense of minimum residual phase variance. It also provides a unified formalism that allows accounting for multi WaveFront Sensors (WFSs) channels, both on Laser Guide Stars (LGSs) and NGSs, and for various disturbance sources (turbulence, vibrations). We show how the specific MOAO CANARY configuration can be embedded in a state-space framework. We present experimental laboratory validations that demonstrate the gain brought by tomographic LQG control for CANARY, together with comparative simulations. Model identification necessary for a robust on-sky operation is discussed.
We present in this paper an analysis of several tip-tilt on-sky data registered on adaptive optics systems installed on different telescopes (Gemini South, William Herschel Telescope, Large Binocular Telescope, Very Large Tele scope, Subaru). Vibration peaks can be detected, and it is shown that their presence and location may vary, and that their origin is not always easy to determine. Mechanical solution that have been realized to mitigate vibrations are presented. Nevertheless, residual vibrations may still affect the instruments' performance, ranging from narrow high frequency vibration peaks to wide low frequency windshake-type perturbations. Power Spectral Densities (PSDs) of on-sky data are presented to evidence these features. When possible, indications are given regarding the gain in performance that could be achieved with adequate controllers accounting for vibration mitigation. Two examples of controller identification and design illustrate their ability to compensate for various types of disturbances (turbulence, windshake, vibration peaks, ...),showing a significant gain in performance.
The effects of pupil motion on retinal imaging are studied in this paper. Involuntary eye or head movements
are always present in the imaging procedure, decreasing the output quality and preventing a more detailed
diagnostics. When the image acquisition is performed using an adaptive optics (AO) system, substantial gain is
foreseen if pupil motion is accounted for. This can be achieved using a pupil tracker as the one developed by
Imagine Eyes R®, which provides pupil position measurements at a 80Hz sampling rate. In any AO loop, there
is inevitably a delay between the wavefront measurement and the correction applied to the deformable mirror,
meaning that an optimal compensation requires prediction. We investigate several ways of predicting pupil
movement, either by retaining the last value given by the pupil tracker, which is close to the optimal solution in
the case of a pure random walk, or by performing position prediction thanks to auto-regressive (AR) models with
parameters updated in real time. We show that a small improvement in prediction with respect to predicting
with the latest measured value is obtained through adaptive AR modeling. We evaluate the wavefront errors
obtained by computing the root mean square of the difference between a wavefront displaced by the assumed
true position and the predicted one, as seen by the imaging system. The results confirm that pupil movements
have to be compensated in order to minimize wavefront errors.
We present the minimum variance control solution for an AO system featuring several NGS/LGS wavefront
sensors operating at different sampling rates. We show that the optimal solution is based on a non-stationary
Kalman filter. A simple sequential implementation is proposed, with one update equation per sensor. A stationary
suboptimal solution is also derived.
Voltage saturation mechanisms are always present on deformable mirrors (DMs) used in adaptive optics (AO)
systems, so as to prevent possibly irreversible degradation of the DM. This may happen most often in a strong
turbulence context, where too high voltage values are computed by control algorithms trying to compensate for
high phase shifts. In minimum variance control, it is well known that input saturation in linear systems destroys
separation, leading to untractable optimal control problems. We show that, in the absence of DM's dynamics,
separation and certainty equivalence hold in AO even when saturations are present on the system. The optimal
control can then be computed by solving a constrained projection problem. As this is computationally intensive,
we also propose a sub-optimal control with lower computational burden, which guarantees optimal estimation of
the turbulent phase. Optimal and suboptimal controls show a dramatic improvement in performance (measured
by the Strehl ratio) compared with those obtained with integral controllers equipped with adequate clipping and
anti-wind-up mechanisms. All simulation results are obtained in bad seeing conditions using a VLT Paranal type
configuration.
We address the problem of proper handling of deformable mirror (DM) dynamics in Adaptive Optical (AO) systems.
We develop a state-space approach based on a continuous stochastic model of the atmospheric turbulence,
which yields a fully optimal minimum mean-square error (mmse) solution in the form of a discrete-time Linear-Quadratic-Gaussian (LQG) regulator design. This optimal approach provides a reference point for assessing the
performance of simpler suboptimal solutions used up to now. We show the significance of taking into account
the DM dynamics, in particular for the upcoming secondary deformables.
Adaptive Optical systems (AO) with a very large number of degrees-of-freedom (DoF) need the proper development
of reconstruction and control algorithms mingling both increased performance and reduced computational
burden.
The Hartmann wave-front sensor (HS-WFS) is broadly used in AO, featuring a set of lenslet arrays aligned
onto a Cartesian grid. It works by averaging the slope of the wave-front in each sub-aperture. Throughout this
paper the suitability of the so-called Hudgin, Fried and Southwell geometries to model the HS are analysed.
Methods of exploiting data obtained from the telescope's annular aperture through the DFT are revisited.
An alternative approach based upon the discrete Gerchberg iterative algorithm is employed. It inherently solves
the extrapolation and circularization. The inverse problem is regularised to form the minimum mean-square error
(MMSE) reconstructor in the spatial-frequency domain.
Results obtained through Monte-Carlo simulations allow for a comprehensive comparison to the standard
vector-matrix multiplies (VMM/VMMr) algorithm. Computational burden is kept O(DoF log2(DoF)).
Classic Adaptive Optics (AO) is now a proven technique to correct turbulence on earth based astronomical
telescopes. The corrected field of view is however limited by the anisoplanatism effect. Multi-Conjugate AO
(MCAO) aims at providing a wide field of view correction through the use of several deformable mirrors and of
multi-guide-star wavefront sensing. However the performance optimization of such complex systems raises new
questions in terms of calibration and control. We present our current developments on performance optimization
of MCAO systems. We show that performance can be significantly improved with tomographic control based on
Linear Quadratic Gaussian control, compared with more standard methods. An experimental demonstration of
this new approach is going to be implemented on HOMER, the recent bench developed at ONERA devoted to
MCAO laboratory research. We present here results in closed-loop in AO, GLAO and MCAO with an integrator
control. This bench implements two deformable mirrors and a wide field Shack-Hartman wavefront sensor.
The SPHERE (Spectro-Polarimetry High-contrast Exoplanet Research) instrument is an ESO project aiming at
the direct detection of extra-solar planets. It should equip one of the four VLT 8-m telescopes in 2010. The heart of the
SPHERE instrument is its eXtrem Adaptive Optics (XAO) SAXO (SPHERE AO for eXoplanet Observation) subsystem
that should deal with a tight error budget. To fulfil SAXO challenging requirements a mixed control law has been
designed. It includes both an optimized modal gain integrator to control the Deformable Mirror (DM) and a Linear
Quadratic Gaussian (LQG) control law to manage the tip-tilt (TT) mirror and filter possible vibrations. A specific
scheme has been developed to optimize the correction provided by the DM and the TT while minimizing the coupling
between both control loops. Actuator saturation and wind-up effects management are described. We describe the overall
control architecture and focus on these main issues. We present expectable performance and also consider the
interactions of the main control loop with other subsystems.
PUBLISHER'S NOTE Sept. 9, 2010: Due to a production error, SPIE Paper 70151U was inadvertently published also as SPIE Paper 70151D. This has been corrected. This record contains the correct citation, abstract, and manuscript for paper 70151D.
All thing being equal, increasing the sampling rate of a computer-controlled feedback loop extends its effective
bandwidth, and thus the achievable performance in terms of disturbance rejection. This applies to AO systems,
where deformable mirror's (DM) control voltages are computed from wavefront sensor's (WFS) measurements.
However, faster sampling, i.e. shorter exposure time for the WFS's CCD, results (especially for low-flux astronomical
applications) in higher measurement noise, thereby degrading overall performance. A way to circumvent
this limitation is to increase only the DM's control rate. However, standard integral AO control is inherently
ill-suited for such multirate mode, because integrators require an uninterrupted measurement stream to maintain
closed-loop stability. On the other hand, Linear Quadratic Gaussian (LQG) AO control, where DM controls are
computed from explicit predictions of future values of the turbulent phase provided by a Kalman filter, can be
easily adapted to multirate configurations where the WFS sampling period is a multiple of the DM's one, provided
that a stochastic model of the turbulent phase at the fast (DM) rate is available. The Kalman filter, between
two successive measurements, operates in (observer) open-loop mode, with predictions updated by extrapolating
current trends in the turbulent phase's trajectory. Thus, while simple vector-valued AR(1) turbulence models
are sufficient for single-rate LQG AO loops, more complex stochastic models are likely to be needed to achieve
good performance in multirate configurations.
Classic Adaptive Optics (AO) is now successfully implemented on a growing number of ground-based imaging systems.
Nevertheless some limitations are still to cope with. First, the AO standard control laws are unable to easily handle
vibrations. In the particular case of eXtreme AO (XAO), which requires a highly efficient AO, these vibrations can thus
be much penalizing. We have previously shown that a Kalman based control law can provide both an efficient correction
of the turbulence and a strong vibration filtering. Second, anisoplanatism effects lead to a small corrected field of view. Multi-Conjugate AO (MCAO) is a promising concept that should increase significantly this field of view. We have shown
numerically that MCAO correction can be highly improved by optimal control based on a Kalman filter. This article
presents the first laboratory demonstration of these two concepts.
We use a classic AO bench available at Onera with a deformable mirror (DM) in the pupil and a Shack-Hartmann Wave
Front Sensor (WFS) pointing at an on-axis guide-star. The turbulence is produced by a rotating phase screen in altitude.
First, this AO configuration is used to validate the ability of our control approach to filter out system vibrations and improve
the overall performance of the AO closed-loop, compared to classic controllers. The consequences on the RTC design of
an XAO system is discussed. Then, we optimize the correction for an off-axis star although the WFS still points at the
on-axis star. This Off-Axis AO (OAAO) can be seen as a first step towards MCAO or Multi-Object AO in a simplified
configuration. It proves the ability of our control law to estimate the turbulence in altitude and correct in the direction of
interest. We describe the off-axis correction tests performed in a dynamic mode (closed-loop) using our Kalman based
control. We present the evolution of the off-axis correction according to the angular separation between the stars. A highly
significant improvement in performance is demonstrated.
We present a laboratory demonstration of open loop Off-Axis Adaptive Optics with optimal control. The control based on a Minimum Mean Square Error Estimator brings a noticeable performance improvement. The next step will be to close the Off-Axis Adaptive Optics loop with a Kalman based optimal control. While this last experiment is currently under progress, a classic Adaptive Optics loop has already been closed recently with a Kalman based control and experimental results are presented. We also describe the expectable performance of the Kalman based off-axis closed loop thanks to an end-to-end simulator. Last minute notice: the Kalman based Off-Axis Adaptive Optics loop has been closed and very first results are given.
While the first MultiConjugate Adaptive Optics (MCAO) experimental set-ups are presently under construction, a growing attention is paid to the control loop. This is indeed a key element in the optimization process, especially for MCAO systems. Different approaches have been proposed in recent articles for astronomical applications: simple integrator, Optimized Modal Gain Integrator and Kalman filtering. We study here Kalman filtering, which seems a very promising solution.
We have already proposed and simulated in simple cases a formalized adaptation of Kalman filtering to Adaptive Optics (AO) and MCAO. We wish now to characterize for the first time the frequential properties of this Kalman filter and to refine it so as to improve its robustness and performance, for instance in the presence of static aberrations and vibrations. Comparisons with classical controllers are proposed. Aliasing reduction could also be considered. In the near future, Kalman filter performance and robustness should be tested for realistic AO and MCAO configurations on a simulator and an experimental set-up.
We first recall in this paper the optimal closed loop control law for multiconjugate adaptive optics [MCAO]. It is based on a Kalman filter and a feedback control. The prior model on which is based the Kalman filter is developped in a state-space representation and the differences in the model between Star Oriented [SO] MCAO and Layer Oriented [LO] MCAO are presented. This approach allows to take into account the wavefront sensing noise, the turbulence profil model, the Kolmogorov statistics and a temporal model of the turbulence. Simulation results are given in SO MCAO and the Kalman based approach is compared to the more standard Optimized Modal Gain Integrator [OMGI].
We propose in this paper an optimal closed loop control law for multiconjugate adaptive optics (MCAO), based on a Kalman filter and a feedback control. The so-called open loop optimal phase reconstruction is recalled. It is based on a Maximum A Posteriori (MAP) approach. This approach takes into account wavefront sensing noise and also makes use of a turbulence profile model and Kolmogorov statistics. We propose a closed-loop modelization via a state-space representation. A Kalman filter is used for the phase reconstruction. This approach is a closed loop generalization of the MAP open loop estimator. It uses the same spatial prior in addition with a temporal model of the turbulence. Results are compared with the Optimized Modal Gain Integrator approach in the classical adaptive optics case and in an MCAO-like case.
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