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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