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Modelling synthetic atmospheric turbulence profiles with temporal variation using Gaussian mixture model

Jia, Peng; Osborn, James; Kong, Letian; Laidlaw, Douglas; Li, Caifeng; Farley, Ollie; Xue, Gang

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Authors

Peng Jia

Letian Kong

Douglas Laidlaw

Caifeng Li

Ollie Farley

Gang Xue



Abstract

The atmospheric turbulence profile plays a very important role for performance evaluation of wide-field adaptive optic systems. Since the atmospheric turbulence is evolving, the turbulence profile will change with time. To better model the temporal variation of turbulence profile, in this paper, we propose to use the extensive stereo-SCIDAR turbulence profile dataset from one observation site to train a Gaussian mixture model. The trained Gaussian mixture model can describe the structure of the turbulence profile in that particular site with several multidimensional Gaussian distributions. We cluster the turbulence profile data with the Gaussian mixture model and analyse the temporal variation properties of the clusters. We define the characteristic time as the time that the measured turbulence profile remains in a given profile. We find that normally the characteristic time is around 2 to 20 min and will change at different sites and in different seasons. With the statistical results of the characteristic time and the trained Gaussian mixture model, we can generate synthetic artificial turbulence profiles with realistic temporal variation to better test the performance of adaptive optics systems.

Citation

Jia, P., Osborn, J., Kong, L., Laidlaw, D., Li, C., Farley, O., & Xue, G. (2018). Modelling synthetic atmospheric turbulence profiles with temporal variation using Gaussian mixture model. Monthly Notices of the Royal Astronomical Society, 480(2), 2466-2474. https://doi.org/10.1093/mnras/sty1951

Journal Article Type Article
Acceptance Date Jul 19, 2018
Online Publication Date Jul 20, 2018
Publication Date Oct 21, 2018
Deposit Date Aug 20, 2018
Publicly Available Date Aug 21, 2018
Journal Monthly Notices of the Royal Astronomical Society
Print ISSN 0035-8711
Electronic ISSN 1365-2966
Publisher Royal Astronomical Society
Peer Reviewed Peer Reviewed
Volume 480
Issue 2
Pages 2466-2474
DOI https://doi.org/10.1093/mnras/sty1951

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Copyright Statement
This article has been accepted for publication in Monthly Notices of the Royal Astronomical Society ©: 2018 Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.







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