引入时间变量的TLE轨道确定

    TLE Orbit Determination Considering Time Variables

    • 利用TLE数据获得空间碎片的精确轨道信息一直是研究重点. 因缺乏对热层大气的理解, 大气阻力是轨道确定最大的误差来源, 其中大气密度模型、弹道系数中的误差与时间有关, 然而现有基于TLE数据的定轨算法并未考虑与时间相关的误差影响, 导致轨道预报精度无法进一步提升. 因此, 引入时间变量, 利用单纯形调优搜索算法将其与其他轨道参数一同求解, 削弱与时间相关的误差对轨道精度的影响. 使用8颗卫星的TLE数据和CPF精密星历数据开展实验, 引用时间变量的轨道预报相对精度提升了0.11%~78.60%. 因此, 通过引入时间变量削弱与时间变量相关的误差, 有助于提升定轨精度, 研究成果有望在大气再入预报、风险评估、碰撞预警等领域得到应用.

       

      Abstract: To obtain precise orbit information of space debris from Two-Line Element (TLE) has always been a research focus. Due to a lack of understanding of the thermosphere atmosphere, atmospheric drag is the largest source of error in orbit determination, with errors in atmospheric density models and trajectory coefficients being time-dependent. However, TLE-based orbit determination algorithms have not taken into account the impact of time-dependent errors, resulting in the inability to further improve orbit prediction accuracy. Therefore, this article introduces a time variable and uses the simplex optimization search algorithm to solve it together with other orbit parameters, weakening the impact of time-related errors on orbit accuracy. This article conducted experiments using TLE data and CPF (Consolidated Prediction Format) precise ephemeris data from 8 satellites, and the relative accuracy of orbit prediction considering time variables was improved by 0.11%~78.60%. Therefore, introducing time variables to weaken errors related to time variables can help improve orbit determination accuracy, and research results are expected to be applied in fields, such as atmospheric re-entry forecasting, risk assessment, collision warning, etc.

       

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