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Journal Articles Monthly Notices of the Royal Astronomical Society Year : 2019

Estimation of atmospheric turbulence parameters from Shack-Hartmann wavefront sensor measurements

Paulo P. Andrade
  • Function : Author
Paulo J. V. Garcia
  • Function : Author
Johann Kolb
  • Function : Author
Maria Inês Carvalho
  • Function : Author

Abstract

The estimation of atmospheric turbulence parameters is of relevance for the following: (a) site evaluation and characterization; (b) prediction of the point spread function; (c) live assessment of error budgets and optimization of adaptive optics performance; (d) optimization of fringe trackers for long baseline optical interferometry. The ubiquitous deployment of Shack-Hartmann wavefront sensors in large telescopes makes them central for atmospheric turbulence parameter estimation via adaptive optics telemetry. Several methods for the estimation of the Fried parameter and outer scale have been developed, most of which are based on the fitting of Zernike polynomial coefficient variances reconstructed from the telemetry. The non-orthogonality of Zernike polynomial derivatives introduces modal cross coupling, which affects the variances. Furthermore, the finite resolution of the sensor introduces aliasing. In this article the impact of these effects on atmospheric turbulence parameter estimation is addressed with simulations. It is found that cross-coupling is the dominant bias. An iterative algorithm to overcome it is presented. Simulations are conducted for typical ranges of the outer scale (4-32 m), Fried parameter (10 cm) and noise in the variances (signal-to-noise ratio of 10 and above). It is found that, using the algorithm, both parameters are recovered with sub-per cent accuracy.
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Dates and versions

insu-03666773 , version 1 (12-05-2022)

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Paulo P. Andrade, Paulo J. V. Garcia, Carlos M. Correia, Johann Kolb, Maria Inês Carvalho. Estimation of atmospheric turbulence parameters from Shack-Hartmann wavefront sensor measurements. Monthly Notices of the Royal Astronomical Society, 2019, 483, pp.1192-1201. ⟨10.1093/mnras/sty3181⟩. ⟨insu-03666773⟩
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