基于改进的无迹卡尔曼滤波确定视线感知相对状态  

Determination of vision-based relative state by modified unscented Kalman filter

作　　者：王晓初[1] 尤政[1] 赵开春[1] 

机构地区：[1]清华大学精密测试技术及仪器国家重点实验室,北京100084

出　　处：《光学精密工程》2013年第4期1032-1039,共8页Optics and Precision Engineering

基　　金：中国博士后科学基金特别资助项目(No.201104127)

摘　　要：基于视线传感器原理,研究了如何确定摄动作用下两颗卫星间相对状态的问题。采用VISNAV传感器作为相对状态传感器,并应用一种改进滤波算法实现了问题求解。首先,考虑了两颗卫星间相对位置与相对姿态的运动方程及摄动作用的影响,给出了改进的离散系统方程及其误差协方差矩阵的取值方法,避免了复杂协方差矩阵的实时额外求解,降低了算法计算量及实施难度。最后,给出相应的无迹卡尔曼滤波(UKF)算法并通过STK和MATLAB软件进行了数值仿真实验。分析表明,改进后的算法保证了收敛性,数值仿真及对比仿真验证了本文方法的可行性和有效性。在摄动因素作用的前提下,改进的方法能够在200m的相对距离内达到角秒级的相对姿态确定精度和毫米级的相对位置确定精度,完全可以满足近距离自由飞行卫星间的相对状态确定要求。Abstract： On the basis of the principle of a VISNAV sensor, this paper researches how to determine the vision-based relative state between two satellites with disturbances. By taking the VISNAV sensor as a relative state sensor, the problem mentioned above is solved by a modified Kalman filter algo- rithm. In consideration of the relative orbit dynamics equation with disturbance and the relative atti- tude kinematic equation, it gives modified discrete equation and a calculation method for the error co- variance matrix. By which the method avoids the complicated real-time operations of large dimensional matrices in every loop and reduces computation amounts. Finally, the corresponding modified Un- scented Kalman Filter （UKF）method followed by a numerical simulation experiment is performed un- der STK and MATLAB. Results demonstrate that the method is feasible, effective and has good con- vergence. Under disturbance condition, its determination accuracy in 200 m is an angle second level for the relative attitude and a millimeter level for the relative position, which meets the requirements of determining the relative state between two satellites in a shorter distance.

关 键 词：视线传感器 相对状态确定 摄动 改进的无迹卡尔曼滤波 

分 类 号：V412.42[航空宇航科学与技术—航空宇航推进理论与工程] V474.1