基于DR/CNS的月球车位置估计方法  

An Approach of DR/CNS Based on Position Estimation of Lunar Rover

作　　者：刘洋波[1] 刘红云[1] 裴福俊[1] 居鹤华[1] 

机构地区：[1]北京工业大学电控学院,北京100124

出　　处：《计算机测量与控制》2011年第12期3057-3059,3063,共4页Computer Measurement &Control

基　　金：国家863高技术研究计划(2006AA12Z307)

摘　　要：月球车自主导航系统是完成月球探测任务的基础和关键,文中针对月球车导航的特殊要求设计了一种基于CNS/DR组合的月球车自主导航方法;首先依据月球车运动模型建立了系统状态方程,然后利用太阳敏感器测量的太阳高度角、航位推算系统输出的航向角速率和单位时间间隔内月球车行进距离作为量测信息建立了导航系统观测方程,再用扩展卡尔曼滤波(EKF)对导航信息进行最优估计;最后,对基于CNS/DR组合的月球车自主导航方法在计算机上进行了仿真分析;通过仿真结果可以说明文中提出的方法能获得较好的位置和航向估计精度,证明了该方法的正确性,是解决月球车自主导航问题一种有效的方法。The autonomous navigation system !s very fundamental and important to the lunar rover to complete the lunar exploration mission, so the CNS/DR based autonomous navigation system of lunar rover has been designed under the very spaical navigation enviroment. In this paper, a new approach of autonomous navigation for lunar rover based on Extended Kalman Filter （EKF） was described. The principle of this method was introduced, and the state space equation of system for lunar rover based on the rover motion model was developed. Then three measurements be implemented for observation vector, they are the elevation of sun that observed by sun sensor, angular velocity on the yew direction and lunar rover moving distance in a unit time step, that both the output of DR navigation system. The EKF has been implemented to get the optimal estimation of navigation information. Finally, the simulation of this method was finished. A simulation results demonstrated that this approach not only has good precision of position andhead angle, but also the effective solution of lunar rover autonomous navigation.

关 键 词：月球车 太阳敏感器 天文导航 航位推算 扩展卡尔曼滤波 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]