Computer Science
Scientific paper
Aug 2006
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006spie.6316e...1l&link_type=abstract
Image Reconstruction from Incomplete Data IV. Edited by Bones, Philip J.; Fiddy, Michael A.; Millane, Rick P.. Proceedings of t
Computer Science
Scientific paper
We have investigated seasonal turbulence variation with altitude above the Siding Spring Observatory using the 24" telescope facility and interchangeable SCIDAR (Scintillation Detection and Ranging) and SLODAR (Slope Detection and Ranging) techniques. The latter proposed by Wilson triangulates the correlations through image motion of and between images of binary stars when imaged through multiple sub-pupils in a Shack-Hartmann configuration, so to determine the C2N(h) profile as a function of height above the telescope, and temporal evolution from subsequent short exposure, fast frame rate images. The simplicity of SLODAR pertains to the lack of restriction in coherence or fringe visibility (scintillation index) that underlies the SCIDAR technique, and that the available light is divided into N sub-pupils to be condensed to speckle star images, rather than spread across the full imaging array. However, with the like of f18 telescope being reduced in each sub-pupil to f60, using a 1-4 ms exposure intensified imager, we are still limited to magnitude 5-7 star pairs, of which there are precious few, and their associated angular separations limit the altitude resolution of the technique accordingly. To overcome some of these restrictions we have obtained data, and propose methods to process such, using the Galilean satellites of Jupiter (each mag 5-6), which change separation over the observing cluster of nights, and hence offer a changeable altitude sampling. These are unresolvable in the sub-pupil imaging system, but suffer less from the speckling effects of a scintillated point source. We present results to reinforce these premises.
Goodwin Michael
Jenkins Charles
Lambert Andrew
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