Atmospheric turbulence profiling with a Shack-Hartmann wavefront sensor

Hajime Ogane*, Masayuki Akiyama, Shin Oya, Yoshito Ono

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

In order to measure the altitude profile of the atmospheric turbulence in real-time, we are applying a MASSDIMM method (Multi Aperture Scintillation Sensor and Differential Image Motion Monitor) to the ShackHartmann wavefront sensor data. Tomographic estimation of the atmospheric turbulence is a key technique in new generation of adaptive optics systems with multiple guide stars, and the real-time turbulence profiling provide a useful prior information for the tomography, which is an ill-posed inverse problem. By using the data of a Shack-Hartmann sensor, a turbulence profile in the same direction as the AO correction can be acquired. Moreover, since more information can be used compared with the traditional MASS-DIMM, the resolution in the height direction can be increased. This time, the data of the Shack-Hartmann sensor attached to Tohoku University 50cm telescope was analyzed, and the estimation of the turbulence profile was obtained. Similar profiles were obtained while the elevation of the star and the apparent distance to the turbulence changed in one hour monitoring measurements. The results supported the validity of the method.

Original languageEnglish
Title of host publicationAdaptive Optics Systems VII
EditorsLaura Schreiber, Dirk Schmidt, Elise Vernet
PublisherSPIE
ISBN (Electronic)9781510636835
DOIs
Publication statusPublished - 2020
Externally publishedYes
EventAdaptive Optics Systems VII 2020 - Virtual, Online, United States
Duration: 14 Dec 202022 Dec 2020

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11448
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceAdaptive Optics Systems VII 2020
Country/TerritoryUnited States
CityVirtual, Online
Period14/12/2022/12/20

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