7 August 2014 Maximum likelihood approach for the adaptive optics point spread function reconstruction
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Abstract
This paper is dedicated to a new PSF reconstruction method based on a maximum likelihood approach (ML) which uses as well the telemetry data of the AO system (see Exposito et al. (2013)1). This approach allows a joint-estimation of the covariance matrix of the mirror modes of the residual phase, the noise variance and the Fried parameter r0. In this method, an estimate of the covariance between the parallel residual phase and the orthogonal phase is required. We developed a recursive approach taking into account the temporal effect of the AO-loop, so that this covariance only depends on the r0, the wind speed and some of the parameters of the system (the gain of the loop, the interaction matrix and the command matrix). With this estimation, the high bandwidth hypothesis is no longer required to reconstruct the PSF with a good accuracy. We present the validation of the method and the results on numerical simulations (on a SCAO system) and show that our ML method allows an accurate estimation of the PSF in the case of a Shack-Hartmann (SH) wavefront sensor (WFS).
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J. Exposito, J. Exposito, Damien Gratadour, Damien Gratadour, Gérard Rousset, Gérard Rousset, Yann Clénet, Yann Clénet, Laurent Mugnier, Laurent Mugnier, Éric Gendron, Éric Gendron, } "Maximum likelihood approach for the adaptive optics point spread function reconstruction", Proc. SPIE 9148, Adaptive Optics Systems IV, 91484P (7 August 2014); doi: 10.1117/12.2055761; https://doi.org/10.1117/12.2055761
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