论文标题
通过采样模拟跨模式和空间相关的Zernike系数来模拟各个方向性的湍流
Simulating Anisoplanatic Turbulence by Sampling Inter-modal and Spatially Correlated Zernike Coefficients
论文作者
论文摘要
模拟大气湍流是评估缓解湍流算法和训练学习方法的重要任务。可用于大气湍流的高级数值模拟器，但是它们需要评估波动传播，这在计算上昂贵。在本文中，我们提出了一种通过湍流模拟成像的无传播方法。我们工作背后的关键思想是一种绘制模式间和空间相关的Zernike系数的新方法。通过建立Basu，McCrae和Fiorino（2015）的到达角度相关性与Chanan（1992）的多孔相关性之间的等价性，我们表明可以根据定义相关性的协变量矩阵来绘制Zernike系数。我们提出了快速，可扩展的采样策略来绘制这些样品。新方法使我们能够将波传播问题压缩为抽样问题，因此使新模拟器明显快于现有模拟器。实验结果表明，模拟器与理论和实际湍流数据具有极好的匹配。
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 evaluating wave propagation which is computationally expensive. In this paper, we present a propagation-free method for simulating imaging through turbulence. The key idea behind our work is a new method to draw inter-modal and spatially correlated Zernike coefficients. 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 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.
