Paper
13 September 2012 Temporal convergence of phase spatial covariance matrix measurements in tomographic adaptive optics
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Abstract
The identification of spatial covariance matrices is required in adaptive optics in order to perform tomographic reconstruction with optimal estimators. We use on-sky measurements from Canary, the on-sky demonstrator of MOAO for EAGLE, to study the statistical convergence of the spatial covariance of Shack-Hartmann measurements. We describe a new, faster, analytical approximated model for this spatial covariance, and finally bring into light a new procedure for model identification, reducing the tomographic error. We quantify the gain brought by the new approach on both numerical simulations and on-sky data.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Olivier Martin, Éric Gendron, Gérard Rousset, and Fabrice Vidal "Temporal convergence of phase spatial covariance matrix measurements in tomographic adaptive optics", Proc. SPIE 8447, Adaptive Optics Systems III, 84472A (13 September 2012); https://doi.org/10.1117/12.924845
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Cited by 10 scholarly publications.
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KEYWORDS
Tomography

Matrices

Adaptive optics

Turbulence

Error analysis

Reconstruction algorithms

Statistical analysis

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