基于图像位移的低轨卫星自主导航技术

利用高速相机测得的地面图形相对卫星的位移,结合星敏感器测得的姿态信息,基于卫星相对地面的速度是一个非线性变化过程这一事实,实现低轨卫星的自主导航.相对于传统的陆标识别自主导航,该方法不需识别地面物体或景象,只需利用图像之间的位移关系,经相关性分析后,便可获得卫星相对于地面的速度信息.因此,不需要存储地面物体或景象的先验信息,故减轻了存储负担.文中还构建了系统的状态方程和量测方程,采用卡尔曼滤波器进行信息滤波.仿真分析显示,该系统具有较好的自主导航精度,可以应用于低轨卫星的自主导航.

LEO AUTONOMOUS NAVIGATION BASED ON IMAGE MOTION

A method of LEO autonomous navigation is presented based on the nonlinear satellite velocity relative to the earth. The velocity is detected by a high-speed camera, with the attitude information detected by a star sensor. Compared with traditional autonomous navigation by landmark identification, the satellite velocity relative to the earth is obtained by correlativity analysis of images. It does not need to recognize ground objects or views. Since it is not necessary to pre-store the database of ground marks, lots of memory space can be saved. The state and observation equations are constructed, and the filtering is processed by the Kalman filter. Simulation results show that the system has high autonomous navigation precision in LEO autonomous navigation.