航天器轨道机动过程中的自主导航方法

An Autonomous Navigation Method for Spacecrafts during Orbit Maneuver

典型的航天器自主天文导航方法利用地球敏感器和星敏感器的观测信息,根据轨道动力学模型和测量信息,采用扩展卡尔曼滤波算法(EKF)估计航天器位置矢量。为了在航天器轨道机动过程中减小滤波器的估计误差,设计了用于航天器自主导航的自适应鲁棒扩展卡尔曼滤波(AREKF)算法。仿真结果表明,采用AREKF算法能够有效地减小推力不确定性的不利影响,在不增加导航敏感器的前提下改善系统的导航性能,取得优于传统EKF算法和自适应扩展卡尔曼滤波(AEKF)的估计精度。

A standard autonomous astronomical navigation method is based on the information of the earth sensor and the star sensor. The extended Kalman filter （EKF） is implemented to estimate the position vector of the spacecraft according to the spacecraft dynamics model and the measurements from these sensors. In order to decrease the estimation error of the filter during orbit maneuvers of the spacecraft, an adaptive robust extended Kalman filter （AREKF） is designed for spacecraft autonomous navigation. The simulation results show that the AREKF can effectively depress the unfavorable effect of thrust uncertainties, and the navigation performance is improved effectively without additional sensors. The estimate of the AREKF is more accurate than ones of the EKF and the adaptive extended Kalman filter （AEKF）