基于补偿最小二乘估计法的卫星精密定轨方法

由于卫星轨道观测数据中含有非线性影响因素，必然会降低定轨精度。将半参数回归模型引入卫星批处理定轨方法中，基于半参数回归模型补偿最小二乘估计法，提出了一种卫星事后轨道改进方法，以降低非线性影响并提高定轨精度。当测量数据存在非线性影响因素时，在理论上证明了半参数回归模型补偿最小二乘估计法优于经典最小二乘估计法。最后，对中低轨卫星定轨进行了仿真，结果表明基于半参数回归模型补偿最小二乘估计法的卫星事后轨道改进方法分离出观测数据中的非线性影响因素，从而提高定轨精度。

Satellite precise orbit determination method based on penalized least squares estimation

The nonlinear factors that exist inevitably in the observations of the satellite will reduce the accuracy of orbit determination.Through introducing the semi-parametric regression model to batch processing,the precise orbit determination method based on penalized least squares estimation of the semi-parametric regression model(POD-SPRM-PLSE) is proposed to improve the accuracy of orbit determination.Then,the accuracy of POD-SPRM-PLSE is proved to be higher than that of the classical batch processor in theory under the situation that observations of satellite exist nonlinear errors.Finally,the simulation on orbit determination of low earth orbit satellites shows that POD-SPRM-PLSE can separate the white noise and nonlinear errors,and improve the accuracy of orbit determination greatly.