摘要
月球车导航传统方法主要是采用Kalman滤波方法,需要对系统方程和观测方程的线性化。因此会引入的线性化误差的问题。针对做出适当的改进,采用UKF方法作为误差状态量的最优估计方法,并以太阳敏感器观测得到的太阳高度角和太阳方位角以及测速仪的东向北向速度作为联合观测信息,将SINS和CNS所测得的月球车相关姿态和位置信息进行数据融合,估计出组合导航系统的误差状态量,从而对惯导系统的状态量进行校正,达到提高组合导航系统的导航定位精度和稳定性,减小线性化误差的目的。仿真实验证明,算法具有很好的位置、速度和姿态估计精度,有效地降低了线性化误差。
The traditional lunar rover navigation estimating methods are the use of Kalman filter, which is ap- propriate for the situation of that both of the linearized system equation and observation equation. So the linearization error will be introduced to the entire system. Appropriate improvements for this problem are maken. The autono-mous navigation method for lunar rover is based on velocity and celestial joint observation. And these observations are used to estimating the lunar rover attitude and position, which will greatly reduce the linearing error and accumulated error. Unscented Kalman filter is used properly to implement optimization estimation in this method. Finally, the simulation results of SIN/CNS demonstrate the validity and feasibility of this method for lunar rover system.
出处
《科学技术与工程》
北大核心
2012年第24期6102-6106,共5页
Science Technology and Engineering
关键词
月球车
自主导航
天文导航
捷联惯性导航
UKF
lunar rover autonomous navigation celestial navigation strapdown inertial navigation UKF
