Simulating Anisoplanatic Turbulence by Sampling Correlated Zernike Coefficients

Abstract

Simulating atmospheric turbulence is an essential task for evaluating turbulence mitigation algorithms and training learning-based methods. Advanced numerical simulators for atmospheric turbulence are available, but they require sophisticated wave propagations which are computationally very expensive. In this paper, we present a propagation-free method for simulating imaging through anisoplanatic atmospheric turbulence. The key innovation that enables this work is a new method to draw spatially correlated tilts and high-order abberations in the Zernike space. By establishing the equivalence between the angle-of-arrival correlation by Basu, McCrae and Fiorino (2015) and the multi-aperture correlation by Chanan (1992), we show that the Zernike coefficients can be drawn according to a covariance matrix defining the spatial correlations. We propose fast and scalable sampling strategies to draw these samples. The new method allows us to compress the wave propagation problem into a sampling problem, hence making the new simulator significantly faster than existing ones. Experimental results show that the simulator has an excellent match with the theory and real turbulence data.