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Automated wind velocity profiling from adaptive optics telemetry
Author(s) -
Douglas J. Laidlaw,
James Osborn,
Tim Morris,
Alastair Basden,
É. Gendron,
Gérard Rousset,
Matthew J. Townson,
Richard Wilson
Publication year - 2019
Publication title -
monthly notices of the royal astronomical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.058
H-Index - 383
eISSN - 1365-2966
pISSN - 0035-8711
DOI - 10.1093/mnras/stz3062
Subject(s) - physics , wind speed , remote sensing , telescope , sky , adaptive optics , telemetry , centroid , temporal resolution , profiling (computer programming) , software , meteorology , optics , aerospace engineering , computer science , geography , operating system , artificial intelligence , programming language , engineering
Ground-based adaptive optics (AO) systems can use temporal control techniques to greatly improve image resolution. A measure of wind velocity as a function of altitude is needed to minimize the temporal errors associated with these systems. Spatio-temporal analysis of AO telemetry can express the wind velocity profile using the SLODAR technique. However, the limited altitude-resolution of current AO systems makes it difficult to disentangle the movement of independent layers. It is therefore a challenge to create an algorithm that can recover the wind velocity profile through SLODAR data analysis. In this study we introduce a novel technique for automated wind velocity profiling from AO telemetry. Simulated and on-sky centroid data from CANARY - an AO testbed on the 4.2 m William Herschel telescope, La Palma - is used to demonstrate the proficiency of the technique. Wind velocity profiles measured on-sky are compared to contemporaneous measurements from Stereo-SCIDAR, a dedicated high-resolution atmospheric profiler. They are also compared to European centre for medium-range weather forecasts. The software package that we developed to complete this study is open source.

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