摘要
针对MEMS传感器精度低、误差大等缺点,采用三轴加速度计、三轴磁强计和三轴陀螺仪进行组合姿态测量,使用卡尔曼滤波进行多传感器数据融合.将旋转矢量法解算出的陀螺仪的姿态四元数作为卡尔曼滤波的预测矢量,将高斯牛顿法解算出的加速度计和磁强计的姿态四元数作为卡尔曼滤波的观测矢量,建立卡尔曼传播方程,求出更高精度的姿态四元数,解算出姿态角,将AHRS中的姿态角与车辆的坐标系对应,实验结果表明车辆在不同状态下的姿态角度变化与车辆的运行状态一致.
In view of the MEMS sensors’ low precision and large errors, three-axis accelerometer, three-axis magnetometer and three-axis gyroscope are combined to measure attitude. And Kalman filter are used for multi-sensor data fusion. The gyroscope’s attitude quaternion calculated by rotation vector becomes a predictive vector of Kalman filter. The accelerometer and magnetometer’s attitude quaternion calculated by Gauss-Newton method becomes a observation vector of Kalman filter. Kalman propagation equation is established to obtain more accurate attitude quaternion to calculate the attitude angle and correspond the attitude angle in AHRS with the vehicle’ attitude angle. Experimental results show that the changed attitude angle of the vehicle coincides with the different states of the vehicle state.
出处
《计算机系统应用》
2014年第8期84-89,共6页
Computer Systems & Applications
基金
国家自然科学基金(51278058)
