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陀螺仪的漂移、载体的线性加速度和周围局部磁场的干扰是制约MARG传感器姿态测量精度的主要问题,传统的方法利用滤波算法和零速修正技术来减小姿态测量误差。该文基于已有的惯性测量单元,设计了一个基于四元数的扩展Kalman滤波器,通过建立MARG传感器模型,引入传感器偏差补偿和自适应的测量噪声协方差矩阵构造方法来提高姿态测量精度,减小载体线性加速度和周围局部磁场的干扰,实现三自由度的姿态测量。基于惯性测量单元(IMU)的实验结果表明了本文所提算法能显著提高姿态测量精度。
Gyro drift, linear acceleration of the carrier and interference of the local magnetic field around it are the main problems that restrict the attitude measurement accuracy of the MARG sensor. The traditional method uses the filtering algorithm and the zero-speed correction technique to reduce the attitude measurement error. In this paper, an extended Kalman filter based on quaternion is designed based on the existing inertial measurement unit. The MARG sensor model is built, the sensor offset compensation and adaptive measurement noise covariance matrix construction method are introduced to improve the attitude measurement precision, Reduce the carrier linear acceleration and the surrounding local magnetic field interference, to achieve three degrees of freedom attitude measurement. Experimental results based on inertial measurement unit (IMU) show that the proposed algorithm can significantly improve the attitude measurement accuracy.