基于低轨卫星星载GPS数据与星历资料反演热层大气密度的研究

In spite of the distinct predominance of space-borne accelerometer in retrieving thermospheric mass density, only the Swarm Mission is still on-orbit who is equipped with this device (CHAMP,GRACE as well as GOCE had fallen down),which greatly limits the global mass density observation coverage in a wide variety of space weather conditions. At present, a large number of Low earth orbiters carry the GPS devices on board, and the GPS ephemerides as well as clock error have improved considerably in accuracy and timeliness, which creates favorable conditions for global intensive observations of the atmospheric mass density. The research project starts with batch processing of space-borne GPS data, analyses the effects of adjusting the predicted values from atmospheric empirical models by using pseudo-stochastic parameters, proposes methods of making detection of the distortion parameters, then discusses to construct forecast equations based on temporal correlation of atmospheric mass density variations, corrects the predicted mass density values based on epoch-by-epoch filter in near real-time model, further analyses the numerical methods of calculating mass density from LEO ephemeris, realizing thermospheric density derivation based on three modes, namely subsequent mode,near real-time mode and LEO ephemerides,which is further used for empirical model calibration. This research has important application value in improving the orbit accuracy of medium and long-term prediction,developing the technologies of satellite autonomous attitude control as well as studying space collision avoidance, etc.

尽管星载加速度计在提取热层大气密度方面优势显著，但目前仅有Swarm卫星搭载有此设备且在轨飞行(CHAMP、GRACE、GOCE已陨落)，极大限制了各种空间天气状况下的观测覆盖范围。当前，众多低轨卫星都搭载有高精度的GPS接收设备,相关星历与钟差产品的精度及其时效性也大幅提高，为全球大气密度加密观测创造了条件。课题从星载GPS数据批处理方式入手，分析采用伪随机参数修正大气密度模型预报值的效果，提出检测失真参数的方法；之后探讨基于大气密度变化时域相关性构建预报方程，以逐历元滤波方式近实时修正模型预报值；继而研究采用几何学星历资料解算大气密度的数值算法与适用性，实现分别基于事后、近实时以及星历资料三种方式反演大气密度，并用于修正大气密度经验模型。课题开展对提高低轨卫星中长期轨道预报精度、发展卫星自主姿控以及研究空间碰撞规避等都有重要的应用价值。

尽管星载加速度计在提取热层大气密度方面优势显著，但目前仅有Swarm与GRACE-FO卫星搭载有此设备且在轨飞行(CHAMP、GRACE、GOCE已陨落)，极大限制了各种空间天气状况下的观测覆盖范围。当前，众多低轨卫星都搭载有GPS接收设备,相关星历产品的精度及其时效性也大幅提高，为全球大气密度加密观测创造了条件。课题探讨分别基于伪随机参数批处理、逐历元滤波以及直接采用星历资料三种方式反演大气密度的算法。针对不同空间天气环境，分析伪随机参数的函数形式、分段时长以及先验信息的最优设置方案，提出了检测失真伪随机参数的方法；在近实时经验模型修正方面，研究基于逐历元滤波方式改正密度模型预报值，借助主成分分析法将一个太阳活动周期内的全球热层密度分布时序矩阵进行奇异值分解，并将经验模型简化表示为若干个正交基函数的线性组合，极大减少了待估参数的个数。为使经验模型误差能与空间天气环境变化相关联，以线性映射的方式将选取的太阳辐射与地磁指数等外部输入量作为扰动因素，改进了预报方程的应用效果，实现了基于少量参数对经验模型的整体校正；设计了基于几何学轨道进行二阶数值差分的算法，经选取合适的采样点时间间隔可获得可靠的非保守摄动加速度，继而反演大气密度。该课题开展对提高低轨卫星中长期轨道预报精度、发展卫星自主姿控以及研究空间碰撞规避等都有重要的应用价值。