Abstract. High-resolution imaging with large ground-based telescopes is limited by atmospheric turbulence. The observed images are usually blurred with unknown point spread functions (PSFs) defined in terms of the wavefront distortions of light. To effectively remove the blur, numerical postprocessing with a good approximation of the wavefront is required. The gradient measurements of the wavefront recorded by Shack–Hartmann wavefront sensor (WFS) can be used to estimate the wavefront. A gradients measurement model for Shack–Hartmann WFS is built. This model is based on the frozen flow hypothesis and uses a least-squares-fit of tip and tilt across the subaperture in the WFS to genarate the averaged gradient measurements. Then a high-resolution wavefront reconstruction method using multiframe Shack–Hartmann WFS measurements is presented. The method uses high cadence WFS data in a Bayesian framework and takes into account the available a priori information of the wavefront phase. Numerical results show that the method can effectively improve the spatial resolution and accuracy of the reconstructed wavefront in different seeing conditions.

中文翻译：

---

使用多帧 Shack-Hartmann 波前传感器测量的高分辨率波前重建

摘要。大型地面望远镜的高分辨率成像受到大气湍流的限制。观察到的图像通常被根据光的波前畸变定义的未知点扩散函数 (PSF) 模糊。为了有效地消除模糊，需要对波前进行良好近似的数值后处理。Shack-Hartmann 波前传感器 (WFS) 记录的波前梯度测量可用于估计波前。建立了 Shack-Hartmann WFS 的梯度测量模型。该模型基于冻结流假设，并使用 WFS 中子孔径的尖端和倾斜的最小二乘拟合来生成平均梯度测量值。然后提出了一种使用多帧 Shack-Hartmann WFS 测量的高分辨率波前重建方法。该方法使用贝叶斯框架中的高节奏 WFS 数据并考虑波前相位的可用先验信息。数值结果表明，该方法能有效提高不同视场条件下重构波前的空间分辨率和精度。