Spectral Power Estimation and Characterization of Unresolved Resident Space Objects

Part of the Air Force space situational awareness mission includes the characterization, identification and real-time tracking of man-made resident space objects (RSO) orbiting the earth. Even with space-based observation, geostationary satellites will be dim and unresolved against a cluttered star or earth limb background. It is critical, therefore, to develop techniques specialized for these conditions. The key required elements include special-purpose time series analysis, a signature database, and physical radiance modeling. For this situation, an extensive database of model signatures is necessary to detect the spectral features of a measured signal and relate them to real physical characteristics. Radiometric accuracy is necessary to generate an effective RSO catalog for target ID and assessment. Spectral Sciences, Inc. proposes an innovative, real-time satellite identification and characterization algorithm based on digital spectral analysis of passive multi/hyperspectral VIS/IR observations of dim and unresolved RSOs. A key innovation of the proposed Spectral Power Estimation and Characterization of Transient Radiance Events (SPECTRE) algorithm is the use of a fast, proven target signature simulation code in conjunction with modern signal processing techniques. Through improvements in satellite identification and characterization, this proposed effort would enhance the overall Air Force SSA mission.