Fingerprinting of Non-resolved Three-axis Stabilized Space Objects Using a Two-Facet Analytical Model

摘要

This approach to resident space object (RSO) fingerprinting is motivated by the established framework of biometric fingerprinting which comprises a basic differentiator, followed by three levels of matching. Level 0 (L0) features would be the size and type of the fingerprint. Level 1 (L1) features are the macro characteristics of the fingerprint. Level 2 (L2) features are locations where a single ridge in the fingerprint splits into two branches or where two branches converge into one. Level 3 (L3) features describe the periodic pattern in the fingerprint. Match at each level provides progressively higher confidence. Correspondingly, the RSO fingerprinting can be considered to comprise matching at a base level, followed by three levels of features. L0 consist of sentinel features such as the gross brightness, and contrast, shape and position of principal specular glints. L1 features comprise the geometric shape of the signature brightness and its color indices. This is analytically represented using a polynomial in the cosine of the sub-solar angle, which captures the effect of the seasons. The Level 2 captures the intrinsic character of the sloping regions or bifurcations in the signature brightness and color. It is used to separate the contribution of the solar panel and body. Level 3 consists of the temporal evolution of the fractional abundance of the solar panel and the body. This allows inference on the mechanical stability and basic information about the attitude of the RSO. A collection of L0 to L3 features for an RSO is thus defines its fingerprint.