Prediction of satellite EDR taxonomy from TLE data and simplified atmospheric density model

The satellite energy dissipation rate (EDR) taxonomy can provide more accurate observation requirement assignment, which can improving the utilization of available resources (radar and optical sensor) of space surveillance network (SSN) in an economical way. To improve the performance of the TLE-based (two-line element) EDR taxonomy, a simplified atmospheric density model is utilized to adjust the satellite EDR that obtained from the TLE-based EDR calculation approach. To verify the validity of this model, the atmospheric density from altitude 340km to 360km that obtained by this simplified atmospheric density model is compared with the real measured data of satellites GRACE and CHAMPA. The adjusted satellite EDR taxonomy results are compared with the reported ones to verify the performance of the proposed approach. Comparison results show that this approach halve the misclassification of TLE-based satellite EDR taxonomy approach. We also analyzed the impact of epoch interval of TLE data on EDR taxonomy misclassification, and verified the existence of the trade-off setting parameter between increasing and decreasing the epoch interval of TLE data. We also provided a simulation to unveil the strong correlation between the atmospheric density and the EDR Taxonomy on a one-year scale, which verifies the necessity of satellite EDR adjustment in satellite EDR taxonomy predication in another aspect.