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    Evaluation of GLO: a Solar Occultation Instrument for Measuring Atmospheric Trace Species on CubeSat Missions

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    Date
    2017-06-09
    Author
    Rosich, Garrett Kyle
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    Abstract
    CubeSats provide an inexpensive means for space-based research. However, optimal mission design depends on minimizing payload size and power. This thesis investigates the GLO (GFCR (Gas Filter Correlation Radiometry) Limb Occultation) prototype, a new small-form-factor design that enables sub-kilometer resolution of the vertical profile of atmospheric trace species to determine radiative influences. This technology improves SWAP (Size, Weight, And Power) over heritage SOFIE and HALOE instruments and provides a cost-effective alternative for solar occultation limb monitoring. A python script was developed to analyze solar intensity through GLO telescope channels. Non-uniform aerosol images used a peak intensity algorithm compared to the edge detection function designed for GFCR channels. Scaling corrections were made for beam splitter inaccuracy and SNR was characterized for frame collection. Different cameras were tested to weigh accuracy versus cost of a camera baffle. Using the Langley plot method, solar intensity versus changes in the solar zenith angle were measured for extrapolation of optical depths. AERONET, a network of ground-based sun photometers measuring atmospheric aerosols, was used for aerosol optical depth validation. Spectral Calculator transmission data allowed for GFCR vacuum channel comparison, gas cell spectral analysis, and gas cell to vacuum channel optical depth examination. Ground testing provided promising results with the low-cost prototype. It will be further evaluated through a balloon flight demonstration using a flight-ready GLO instrument. Additionally, analysis for the DUSTIE mission is planned and simulated using STK and Matlab. This includes CubeSat bus selection, orbit analysis for occultation occurrences, power budgeting, and communication capabilities.
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    http://hdl.handle.net/10919/78013
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    • Masters Theses [19662]

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