Scoring sensor observations to facilitate the exchange of space surveillance data. Issue 3 (1st August 2017) - Weigel, M.; Fiedler, H.; Schildknecht, T.
Abstract: In this paper, a scoring metric for space surveillance sensor observations is introduced. A scoring metric allows for direct comparison of data quantity and data quality, and makes transparent the effort made by different sensor operators. The concept might be applied to various sensor types like tracking and surveillance radar, active optical laser tracking, or passive optical telescopes as well as combinations of different measurement types. For each measurement type, a polynomial least squares fit is performed on the measurement values contained in the track. The track score is the average sum over the polynomial coefficients uncertainties and scaled by reference measurement accuracy. Based on the newly developed scoring metric, an accounting model and a rating model are introduced. Both models facilitate the exchange of observation data within a network of space surveillance sensors operators. In this paper, optical observations are taken as an example for analysis purposes, but both models can also be utilized for any other type of observations. The rating model has the capability to distinguish between network participants with major and minor data contribution to the network. The level of sanction on data reception is defined by the participants themselves enabling a high flexibility. The more elaborated accounting model translates the track score to credit points earned for data provision and spend for data reception. In this model, data reception is automatically limited for participants with low contribution to the network. The introduced method for observation scoring is first applied for transparent data exchange within the Small Aperture Robotic Telescope Network (SMARTnet). Therefore a detailed mathematical description is presented for line of sight measurements from optical telescopes, as well as numerical simulations for different network setups.