RICOCHET: Rapid Imaging and Characterization of Space Object Components by Hyperspectral Extraction and Typing.

Hyperspectral and multispectral imaging sensors have enormous potential for space-based characterization and identification of resident space objects (RSOs). Ideally, a spectral sensor will be able to characterize both LEO and deep-space geosynchronous-earth-orbit (GEO) and higher altitude RSOs. The instrument characteristics, band pass region, number of spectral channels, spatial resolution as well as the impact of backgrounds need to be assessed. To meet the need for better space situational awareness of RSOs, Spectral Sciences Inc. (SSI) proposes to develop a new concept for space-based hyperspectral surveillance that will provide spatially resolved or unresolved spectral imagery, leading to material typing of RSOs. In this Phase I SBIR project, we will first evaluate the physics of the varied space environments that will be encountered, including day-time and night-time illumination sources, atmospheric effects and backgrounds. Processing algorithms that account for these effects and extract material information from the data for classification and identification will be evaluated. Based on these analyses, a system level preliminary concept design will be developed. The goal of the Phase I system will be to perform well over the broadest range of operating conditions and RSO parameter space.