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arXiv 1707.02157astro-ph.IMcs.NAmath.NA
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利用未知功率谱密度的大气湍流剖面 profiling

Atmospheric turbulence profiling with unknown power spectral density

University of Helsinki(赫尔辛基大学);Johannes Kepler University(约翰内斯·开普勒大学)

Tapio Helin, Stefan Kindermann, Jonatan Lehtonen, Ronny Ramlau

AI总结:

本文提出一种改进的SLODAR方法,结合未知地面湍流功率谱密度,通过数值模拟验证了其在湍流剖面重建中的有效性。

摘要:

自适应光学(AO)是现代地面光学望远镜中用于补偿大气湍流引起波前畸变的技术。一种从望远镜数据中获取大气信息的方法是所谓的SLODAR,其中大气湍流剖面是基于Shack-Hartmann波前测量的相关数据估计的。这种方法依赖于分层Kolmogorov湍流模型。在本文中,我们提出了一种新的SLODAR概念扩展,通过包含一个接近地面的通用非Kolmogorov湍流层,其功率谱密度未知。我们证明了同时估计地面以上湍流剖面和地面未知功率谱密度的联合估计问题是病态的,并提出了三种数值重建方法。通过数值模拟,我们展示了我们的方法在湍流剖面重建中相比标准SLODAR方法有显著改进。此外,我们的方法可以准确定位非Kolmogorov功率谱密度中的局部扰动。

英文摘要:

Adaptive optics (AO) is a technology in modern ground-based optical telescopes to compensate the wavefront distortions caused by atmospheric turbulence. One method that allows to retrieve information about the atmosphere from telescope data is so-called SLODAR, where the atmospheric turbulence profile is estimated based on correlation data of Shack--Hartmann wavefront measurements. This approach relies on a layered Kolmogorov turbulence model. In this article, we propose a novel extension of the SLODAR concept by including a general non-Kolmogorov turbulence layer close to the ground with an unknown power spectral density. We prove that the joint estimation problem of the turbulence profile above ground simultaneously with the unknown power spectral density at the ground is ill-posed and propose three numerical reconstruction methods. We demonstrate by numerical simulations that our methods lead to substantial improvements in the turbulence profile reconstruction, compared to standard SLODAR-type approach. Also, our methods can accurately locate local perturbations in non-Kolmogorov power spectral densities.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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