摘要
在相对论导航系统中,通过毫角秒恒星角距测量装置获取反映恒星光行差和光线引力偏折变化的恒星角距观测量,利用导航滤波器处理观测量,估计深空探测器在惯性空间的位置和速度矢量,以及敏感器的测量基准偏差。建立了面向导航滤波器设计和系统性能分析的状态和观测方程,根据导航系统的克拉美劳下界(Cramer-RaoLowerBound,CRLB)考察了相对论导航方法用于深空探测的可行性,设计了通过导航滤波器自学习提升相对论导航系统性能的策略。仿真研究表明,对于环绕火星运行的深空探测器,在恒星角距测量精度为1mas的情况下,相对论导航方法能达到百米量级的定位精度水平。为相对论导航方法在深空中的应用提供了支持。
An autonomous navigation method based on the observations of the relativistic perturbations for deep space probes is presented in this paper.The relativistic perturbations including the stellar aberration and the starlight gravitational deflection are new type of celestial navigation measurement,which can provide the kinematic state information of the deep space probes in the inertial frame.In the relativistic navigation system,the position and velocity vectors of the deep space probes,and the measurement bias of the optical sensor can be estimated through measuring the inter-star angle perturbed by the stellar aberration and the gravitational deflection of light with an optical sensor for LOS(line-of-sight)direction with extremely high accuracy.In this paper,the state equation and measurement equation for the design of the navigation filter and the navigation performance evaluation are established.The feasibility of the relativistic navigation method for deep space probes is investigated via the calculation of the Cramer-Rao Lower Bound(CRLB).In addition,the self-learning strategy of the navigation filter is designed to enhance the relativistic navigation performance.It is illustrated through the numerical simulation that,for a Mars-circling probe,the position error of the relativistic navigation method is on the order of 100 m with the inter-star angle measurement accuracy of1 mas.
作者
熊凯
魏春岭
李连升
周鹏
XIONG Kai;WEI Chunling;LI Liansheng;ZHOU Peng(Science and Technology on Space Intelligent Control Laboratory,Beijing Institute of Control Engineering,Beijing 100094,China)
出处
《深空探测学报(中英文)》
CSCD
北大核心
2023年第2期140-150,共11页
Journal Of Deep Space Exploration
基金
国家自然科学基金(U21B6001)。
关键词
深空探测
天文导航
相对论效应
Q学习扩展卡尔曼滤波器
deep space exploration
celestial navigation
relativistic perturbations
Q-learning extended Kalman filter