一种基于温度参数的热层密度修正方法

热层大气的阻力效应是影响低轨航天器大量空间操作的重要因素, 尤其是经验密度模式, 其固有的至少15%的内符合误差已严重制约航天器轨道计算精度的提高. 针对广泛应用的经验密度模式, 选择物理背景简明、关联参数较少的JACCHIA71模式, 以地磁平静条件下的全球散逸层顶温度最小值T_c及125 km高度拐点温度T_x为对象, 建立密度相对于上述温度参数的条件方程, 推导密度相对于温度参数的解析偏导数, 并给出其最小二乘解. 同时, 利用CHAMP卫星数据对模式进行修正, 模式平均误差从40%降低至3%左右. 通过TG01飞行器的轨道预报比较, 修正前后轨道预报位置精度从2 km提升至1 km左右. 经过CHAMP卫星和TG01飞行器的实测数据检验, 验证了修正算法的正确性和有效性. 

A Method of Calibrating Thermosphere Density Based on Temperature Parameters

Thermosphere atmospheric drag is the significant factor affecting most space operations of low Earth orbiter, especially, an inherent 15% formal error of empirical models has become the cumber to improve orbit calculations accuracy. Among the empirical models used in aerospace engineering, JACCHIA71 model, which has relative explicit physical bac kground and less parameters, is selected as a basic model. The temperature T_c and T_x, namely nighttime minimum of the global exospheric temperature and inflection point temperature, are chosen as the estimated parameters during the differential correction. The condition equation of density with respect to these two temperatures is established, and the least square solutions are given as well. The model accuracy improvement is almost enhanced by over an order of magnitude after calibration using CHAMP data. Orbit prediction accuracy of TG01 with the position bias of 2 km is also improved to 1.3 km through temperature corrections using in-site detecting data. All of these case studies validates the effectiveness of the calibration algorithm.