摘要
针对个人定位的需求,提出了基于MEMS惯性传感器的鞋式个人导航系统。利用人体行走过程中脚部与地面相接触的静止时间段,设计了一种以比力模值、比力方差和角速度模值为检测条件的静止检测算法。将静止时间段的解算速度连同方位一起构造量测,然后设计基于卡尔曼滤波器的修正算法,实现了行走过程中累积误差的估计和校正。最后通过矩形路线的行走实验验证了导航算法的有效性和可行性,并指出了进一步的研究方向。
tection criteria based on the acceleration magnitude, acceleration variance and gyroscope magnitude is ana- lyzed. The INS velocity estimated and the orientation are used to construct the measurements during stance phase. An update algorithm based on Kalman filter to estimate and compensate the accumulated error walking is proposed. Finally, the performances of the proposed algorithm are verified by actual walking ment of rectangular closed-loop path. In addition, future research directions are pointed out. Key words： MEMS; personal navigation; stance phase detection; Kalman filtering during experi-
出处
《测控技术》
CSCD
北大核心
2013年第3期138-142,共5页
Measurement & Control Technology
基金
武器装备预研基金资助项目
关键词
MEMS
个人导航
静止检测
卡尔曼滤波
MEMS
personal navigation
stance phase detection
Kalman filtering during experi-
