基于TLE数据的空间目标EDR分类及观测需求计算

根据能量耗散率（EDR）的定义及空间目标的大气阻力摄动加速度公式，推导出一种由卫星两行根数（TLE）数据计算空间目标EDR的方法. 该方法无需计算空间目标弹道系数和大气模型，EDR计算误差可在1%以下，并且运算量极小. 此外，通过空间目标相对轨道的协方差矩阵描述空间目标的定轨精度，并结合扩展卡尔曼滤波方程，提出一种计算平面轨道下不同EDR空间目标的定轨精度-观测需求曲线的方法. 仿真验证了EDR计算方法的有效性，并给出了雷达对不同EDR分类的目标观测时对应的定轨精度-观测需求曲线. 结果表明当观测稀疏时，目标轨道预报误差正比于EDR，而观测较多时，会有观测饱和现象. 

Deriving the Satellite EDR Taxonomy and Observation Requirement from TLE Data

A satellite taxonomy approach was derived from the definition of the satellite energy dissipation rate (EDR) and the atmospheric drag perturbation formula. This approach can group satellites in several EDR bins based on the two-line element (TLE) data. Because it does not need to calculate the satellite's ballistic coefficient and atmospheric density model, this approach can provide results to within an accuracy of 1%. And the computational complexity of this approach is extremely small. Furthermore, an analytical algorithm for calculating the accuracy versus tracking-density curves of the planar orbit satellite was also proposed in this work based on the extended Kalman filter. The orbit determination accuracy of this algorithm was described through the position covariance matrix of the relative orbit. Simulation results indicate the validity of the EDR calculation approach of this algorithm. Finally, the accuracy versus tracking density curve, which indicated the observation requirement, and the corresponding analysis were provided. Simulation results show that the orbital propagation error is directly proportional to EDR when observations are spare, and that the phenomenon of observation saturation when observations are abundant.