Abstract

The point spread function (PSF) is the impulse response of an optical system. PSFs of an adaptive optics system have very strong variations both in temporal and spatial domain and a stable PSF reconstruction algorithm is required to provide prior information for scientific data processing. In this paper, we report our recent progress in developing a framework for PSF modelling with non-parametric model. The non-parametric PSF model uses compressive wavefront sensing method to build PSFs from wavefront measurements. Then a PSF-NET is used to learn map between PSFs estimated from wavefront sensing and PSFs in different field of views in a ground layer adaptive optics system. We use simulated data to test performance of the non--parametric PSF model and the results show its effectiveness.

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