Local, hierarchic, and iterative reconstructors for adaptive optics

MacMartin, Douglas G.

doi:10.1364/josaa.20.001084

Cited by 20 publications

(21 citation statements)

References 14 publications

(20 reference statements)

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“…This provides convergence only in a small number of iterations. Other methods of acceleration include a Fourier-domain (FD) reconstruction [6], a blended FD/ preconditioned conjugate-gradient (FD-PCG) method [7], and a local control approach [8].…”

Section: Introductionmentioning

confidence: 99%

Warm-started wavefront reconstruction for adaptive optics

et al. 2008

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Future extreme adaptive optics (ExAO) systems have been suggested with up to 10 5 sensors and actuators. We analyze the computational speed of iterative reconstruction algorithms for such large systems. We compare a total of 15 different scalable methods, including multigrid, preconditioned conjugate-gradient, and several new variants of these. Simulations on a 128ϫ 128 square sensor/actuator geometry using Taylor frozen-flow dynamics are carried out using both open-loop and closed-loop measurements, and algorithms are compared on a basis of the mean squared error and floating-point multiplications required. We also investigate the use of warm starting, where the most recent estimate is used to initialize the iterative scheme. In open-loop estimation or pseudo-open-loop control, warm starting provides a significant computational speedup; almost every algorithm tested converges in one iteration. In a standard closed-loop implementation, using a single iteration per time step, most algorithms give the minimum error even in cold start, and every algorithm gives the minimum error if warm started. The best algorithm is therefore the one with the smallest computational cost per iteration, not necessarily the one with the best quasi-static performance.

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Section: Introductionmentioning

confidence: 99%

Warm-started wavefront reconstruction for adaptive optics

et al. 2008

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“…Control can then be based on Qx rather than collocated control. This approach is identical in derivation to that in MacMynowski et al [12], and it is motivated by local approaches for computationally efficient sparse reconstruction in adaptive optics estimation [24]. The resulting response distribution to a single segment rotation error is shown in Fig.…”

Section: Local Feedbackmentioning

confidence: 96%

Control of a Hypersegmented Space Telescope

MacMynowski

2012

Journal of Guidance, Control, and Dynamics

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The primary mirror diameter of affordable space telescopes is limited by mass and manufacturing cost. Currently planned optical/near-infrared space telescopes use a segmented primary mirror with relatively few segments and make limited use of real-time position control. However, control can be used as an enabler for a fundamentally different, very highly segmented architecture, leading to a significant reduction in areal density, and hence a significant increase in the realistically achievable diameter of a space telescope. Weight can be reduced by minimizing the structure that supports mirror segments and instead relying on control for overall stiffness. Furthermore, smaller segments can be thinner (hence, lighter) while still providing sufficient internal rigidity. However, with these architectural changes, the control problem involves not only thousands of actuators and sensors but also many lightly damped modes within the control bandwidth. The objective here is to demonstrate that this control problem is solvable by applying a local control approach. This is illustrated for a 30-m-diam primary mirror composed of 12,000 0.3-m-diam segments.

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“…(10). To solve the eigenvalues and eigenvectors of matrix H we need to solve the following 1-D second-order interpolation equation:…”

Section: B Regularized Inverse Filters In the Discrete Cosine Transfmentioning

confidence: 99%

“…Recently Gilles et al 8 and Gilles 9 developed two multigrid preconditioned conjugate-gradient (PCG) methods for extreme AO systems. MacMartin 10 proposed local and hierarchic iterative wave-front reconstructors, and Shi et al 11 validated them at the Palomar Observatory. These wave-front reconstructors can be computed at the cost of O͑n͒ ϳ O͑n 4͞3 ͒.…”

Section: Introductionmentioning

confidence: 99%

Large-scale wave-front reconstruction for adaptive optics systems by use of a recursive filtering algorithm

2005

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We propose a new recursive filtering algorithm for wave-front reconstruction in a large-scale adaptive optics system. An embedding step is used in this recursive filtering algorithm to permit fast methods to be used for wave-front reconstruction on an annular aperture. This embedding step can be used alone with a direct residual error updating procedure or used with the preconditioned conjugate-gradient method as a preconditioning step. We derive the Hudgin and Fried filters for spectral-domain filtering, using the eigenvalue decomposition method. Using Monte Carlo simulations, we compare the performance of discrete Fourier transform domain filtering, discrete cosine transform domain filtering, multigrid, and alternative-direction-implicit methods in the embedding step of the recursive filtering algorithm. We also simulate the performance of this recursive filtering in a closed-loop adaptive optics system.

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Local, hierarchic, and iterative reconstructors for adaptive optics

Cited by 20 publications

References 14 publications

Warm-started wavefront reconstruction for adaptive optics

Warm-started wavefront reconstruction for adaptive optics

Control of a Hypersegmented Space Telescope

Large-scale wave-front reconstruction for adaptive optics systems by use of a recursive filtering algorithm

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