文档介绍：
基于惯性测量器件和编码器的导航算法研
究
杨柯,王旭阳,吴超,葛彤
**
5
10
(上海交通大学船舶海洋与建筑工程学院,上海 200240)
摘要:本文提出了基于扩展卡尔曼滤波和稳态分量校正的导航算法,解决了加速度和角速度
长时间积分后发散的问题。在对惯性测量器件测量误差严密论证的基础上,建立了基于惯性
测量器件随机游走模型的状态误差方程,并推导出状态误差和加速度、角速度稳态分量之间
的关系。采用扩展卡尔曼滤波获得状态误差的最优估计值,并用该最优估计值校正状态量。
为了验证该算法的有效性,采用配备惯性测量器件 IMU7200 和编码器的小车进行了实验。
IMU7200 提供了加速度和角速度的测量值,而编码器提供了速度和位移的观测值。实验结果
表明,该导航算法可以极大地提高姿态跟踪及定位的精度。
关键词:导航算法;扩展卡尔曼滤波;状态误差方程;稳态分量
中图分类号:TP242
15
Navigation algorithm based on inertial measurement device
and encoder
Yang Ke, Wang Xuyang, Wu Chao, Ge Tong
(School of Naval Architecture,Ocean and Civil Engineering,Shanghai Jiao Tong
20
25
30
35
40
University,Shanghai 200240)
Abstract: In order to solve divergence of long time integrate to acceleration and angular velocity, this
paper presented a navigation algorithm based on extended kalman filter and steady-ponent
correct. On the basis of rigorous argument about the sensor measurement error, state error equation
based on random walk of sensor was established, and the relation between state error and steady-state
component of acceleration and angular velocity was also deduced. The extended kalman filter was used
to calculate the optimal estimation of state error, which can be used to correct the predicted value of
state. In order to test the validity of the navigation algorithm, an experiment of a car equipped with
IMU7200 and encoder was cond