Spectral Performance Optimization of Small-Diameter Telescopes for Space Object Detection

Successful tracking and detection of resident space objects (RSOs) requires selection of spectral filters that are capable of compensating for the effects of wavelength dependent atmospheric scattering, and material reflectance properties. When operating in an urban environment such as Atlanta, GA the emitted city light pollution is also an important factor. In this study, we perform a multi-spectral optimization for the Georgia Tech Space Object Research Telescope across the visible through infrared spectrum that accounts for atmospheric turbulence, atmospheric transmission, and background sky radiance. The first contribution of this work is the development of a wavelength-dependent performance metric for the detection of RSOs under different atmospheric conditions. The second contribution is the derivation of a simplified model for light pollution that is based on existing astronomy models. This simplified model accounts for double scattering of light and can be used for adding a light pollution component to sky background results that are generated by complex atmospheric simulation tools. The final contribution is the derivation of novel spectral filters that are tuned to the sub-optimal atmospheric seeing conditions of Atlanta, GA and the RSO materials that are considered in this study. While this study is developed for the geographic region of Atlanta, GA and uses simplified bidirectional reflectance distribution models models for spacecraft materials, the framework is generalizable to different geographic regions, weather conditions, and satellite orientations.