Maximum likelihood approach for the adaptive optics point spread function reconstruction

Exposito, J.; Gratadour, Damien; Rousset, G.; Clénet, Y.; Mugnier, Laurent M.; Gendron, É.

doi:10.1117/12.2055761

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…E.g., the methods in [11,12] rely on WFS data only and take global basis functions for the reconstruction. The method proposed in [17] tries to model the phase power spectrum analytically, and in [8] a maximum likelihood approach for the used covariance matrices is taken. In [19] only open loop data is taken into account and a fine resolution wavefront is created by combining measurements from different timesteps.…”

Section: Introductionmentioning

confidence: 99%

Point spread function reconstruction for single-conjugate adaptive optics on extremely large telescopes

Wagner¹,

Hofer

Ramlau

2018

J. Astron. Telesc. Instrum. Syst.

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Modern Giant Segmented Mirror Telescopes (GSMTs) like the Extremely Large Telescope, which is currently under construction, depend heavily on Adaptive Optics (AO) systems to correct for atmospheric distortions. However, a residual blur always remains in the astronomical images corrected by Single Conjugate AO (SCAO) systems due to fitting and bandwidth errors, which can mathematically be described by a convolution of the true image with a point spread function (PSF). Due to the nature of the turbulent atmosphere and its correction, the PSF is spatially varying, which is known as aniosplanatic effect. The PSF serves, e.g., as a quality measure for the science images and therefore needs to be known as accurately as possible.In this paper, we present an algorithm for PSF reconstruction in directions apart from the guide star direction in an SCAO system adapted to the needs of GSMTs focused on estimating the contribution of the anisoplanatic and generalized fitting error to the PSF. In particular, the PSF reconstruction algorithm for Single Conjugate Adaptive Optics from [24] is combined with an algorithm for time-dependent atmospheric tomography from [21] to obtain a direction dependent reconstruction of the post-AO PSF.Results obtained in an end-to-end simulation tool show a qualitatively good reconstruction of the PSF compared to the PSF calculated directly from the simulated incoming wavefront as well as a stable performance with respect to imprecise knowledge of atmospheric parameters.

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Section: Introductionmentioning

confidence: 99%

Point spread function reconstruction for single-conjugate adaptive optics on extremely large telescopes

Wagner¹,

Hofer

Ramlau

2018

J. Astron. Telesc. Instrum. Syst.

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show abstract

“…During the last 16 years, researchers have worked to incorporate improvements and additional features to Véran's original concept, and have covered problems as the noise estimation for Shack-Hartmann WFS [4], the PSF field dependence [5] , the anisoplanatism effect [6], algorithm optimization [7] and reconstruction for AO Laser Guide Stars systems [8].…”

Section: Introductionmentioning

confidence: 99%

On-sky PSF reconstruction with APETy

et al. 2014

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PSF reconstruction (PSF-R) for AO systems was pioneered by J.P. Veran in 1997 [1] and was successfully demonstrated at CFHT/PUEO. A recent example was presented in the case for the Keck telescope in 2012 [2]. Nevertheless, it has been a constant struggle since to implement these technique as observatory standard. APETy (A PSF Estimation Tool for Yorick) has been developed since 2009 and applied for PSF reconstruction for the Near Infrared Coronograph Imager (NICI) at the Gemini South Observatory based on a 85 element curvature AO system. Using on-sky wavefront sensor data, we estimate the seeing (r0) from deformable mirror commands and reconstruct diffraction limited images (52 mas resulution) with an accuracy of approximately 90% when compared to the science images. APETy is publically available via GitHub (https://github.com/dgratadour/APETy) and can be adapted to other systems. APETy development includes the PSF-R variation proposed by Gendron [3] which proved to be almost 4 times faster than the original approach.

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Zonal representation–based residual-wavefront reconstruction using multiframe Shack-Hartmann measurements

Guo

Zhang

et al. 2015

Opt. Eng

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Maximum likelihood approach for the adaptive optics point spread function reconstruction

Cited by 3 publications

References 7 publications

Point spread function reconstruction for single-conjugate adaptive optics on extremely large telescopes

Point spread function reconstruction for single-conjugate adaptive optics on extremely large telescopes

On-sky PSF reconstruction with APETy

Zonal representation–based residual-wavefront reconstruction using multiframe Shack-Hartmann measurements

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