Laser-Guide Star Point-Spread Function Reconstruction for ELTs


C. Correia (a) , J.-P. Véran (a), B. Ellerbroek (b), L. Gilles (b) and L. Wang (b)




To exploit the maximum potential of Extremely Large Telescopes (ELT), adaptive-optics (AO)-corrected images can be further enhanced by using image restoration techniques. Such techniques rely on accurate knowledge of the point-spread function (PSF) anywhere in the field.

To increase sky-coverage ELTs use laser beacons to probe the three-dimensional atmosphere and multi-conjugate AO to increase correction above the isoplanatic patch. These features translate into three sources of anisoplanatism: 1) focal anisoplanatism known as cone effect 2) angular anisoplanatism due to the difference of the wave-fronts in the LGS and science directions and 3) tip/tilt angular anisoplanatism, on account of the LGS being blind to TT, the latter being estimated from natural GS measurements in different locations in the field.

In our approach, the long-exposure science optical transfer function (OTF) (Fourier transform of the PSF) is estimated as a product of 3 terms: (i) the OTF of a point-source LGS, estimated from system telemetry using Véran’s method, (ii) a model anisoplanatism filter, computed from a high-fidelity numerical simulation to account for the difference between the OTFs for a point-source at the location of the LGS and the science target, and (iii) a tip/tilt/tilt anisoplanatism filter obtained from system and model telemetry, and expressed as a system-to-model OTF ratio.

We present the first stage of the reconstruction, (ii) and (iii) being presented by Gilles in this same conference. Based on [Véran et al 97], we show how to reconstruct the LGS-PSF by de-noising telemetry-accumulated measurements and removing AO-loop specific terms, namely the measurement noise and aliasing components; we present the modifications needed on account of the system size and the optimisations required to accurately reconstruct the PSF. Furthermore, we compare our estimates to those of a high-fidelity Monte-Carlo simulator (MAOS) that can accurately model the PSF in those locations.

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