Paper
26 July 2016 FASS: the full aperture seeing sensor
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Abstract
We describe a novel technique atmospheric turbulence monitoring called FASS (full aperture seeing sensor) based on a low noise CCD detector. The method uses a Fourier processing approach that estimates the spatial frequency distribution of the scintillation images. This frequency approach samples the propagated images along pupil rings, making the frequency transformation circular, avoiding distortions due to the finite nature of the data. It is shown that aspects such as detector exposure time, opto-mechanical stability, detailed modelling of propagation, noise and star chromaticity, must be carefully addressed during the design and calibration stages.

Although only ground conjugation results are presented in this article, the technique is expected to operate in the generalized mode guaranteeing sufficiently large speckles (larger than the detector pixels). Pixel gains and offsets are effectively corrected, so they don’t significantly influence the accuracy of the profile estimation. Temporal correlations are also shown to provide complementary information not only on the layer wind velocity, but a coarse estimation of their altitude.

Factors limiting the accuracy of the method, such as chromaticity, turbulence strength, exposure time and vibrations are discussed. The method provides excellent performance in simulations and encouraging preliminary results from on-sky images acquired and Paranal, Chile. Comparison to coetaneous profiles estimated with the Durham Stereo-SCIDAR instrument (DSS) are analysed.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. Guesalaga, S. Perera, J. Osborn, M. Sarazin, B. Neichel, and R. Wilson "FASS: the full aperture seeing sensor", Proc. SPIE 9909, Adaptive Optics Systems V, 99090H (26 July 2016); https://doi.org/10.1117/12.2232012
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CITATIONS
Cited by 2 patents.
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KEYWORDS
Sensors

Telescopes

Turbulence

Speckle

Scintillation

Stars

Decision support systems

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