摘要
针对惯性导航系统动基座初始对准问题,提出了一种视觉辅助的惯导系统动基座初始对准方法。建立了视觉与惯导系统测量模型,考虑了特征点位置已知和未知两种情形,分别推导了视觉和惯导系统姿态位置间的关系,设计了EKF滤波器。建立了两种情形下的滤波观测方程,设计了晃动基座初始对准仿真实验,结果表明在视觉特征点位置已知和未知两种条件下,滤波器状态均能收敛,特征点位置已知时收敛时间小于30 s,特征点位置未知时收敛时间约为300 s;在陀螺零偏为0.01(°)/h、加速度计零偏为50μg的仿真条件下,对准精度为水平姿态角优于0.004°,方位角优于0.06°。提出的视觉辅助惯导系统动基座初始对准是一条较新且可行的思路。
Inertial navigation system(INS) alignment on moving base is a difficult task. This paper proposes a vision aided alignment method for INS on moving base. The measurement model of vision aided INS is established. Considering the two cases that the positions of the vision character points are known or not, the relationships between the attitude and position measurements for the vision system and the INS are deduced respectively An extended kalman filter(EKF) is designed for the alignment, and the EKF observations for both cases are given separately. Alignment simulations on swinging base were performed. Results show that in both cases the states converge and the convergence times are less than 30 s and about 300 s respectively. In the simulations the INS is supposed to be consisted of gyroscopes with bias 0.01 (°)/h and accelerometers with bias 50μg, and the INS alignment acquire results with precision of 0.004° for the level attitude and 0.06° for the azimuth. The proposed method gives a new and feasible way for the INS alignment on moving base.
出处
《中国惯性技术学报》
EI
CSCD
北大核心
2014年第4期469-473,共5页
Journal of Chinese Inertial Technology
基金
国家自然科学基金(11072263))
关键词
惯性导航系统
初始对准
动基座
视觉
Alignment
Computer vision
Extended Kalman filters
Navigation
Vision