基于MEMS传感器的高精度姿态角测量研究

发布时间：2018-02-11 20:11

本文关键词： 姿态解算运动加速度互补滤波卡尔曼滤波 MEMS传感器　出处：《中国测试》2017年02期 　论文类型：期刊论文

【摘要】：针对传统姿态参考系统姿态解算容易受到载体运动加速度的干扰,导致系统精度变低、稳定性变差等问题,提出一种改进的卡尔曼滤波算法。该算法建立基于四元数的惯性系统姿态解算数学模型,并根据载体运动加速度的大小,适时调整卡尔曼滤波器的量测噪声方差的大小,以此减弱卡尔曼滤波过程中运动加速度对姿态角解算精度的影响。采用MEMS三轴陀螺仪、加速度计和磁阻传感器完成载体在电梯升降过程中的测量,对实验测量数据进行姿态解算,结果表明改进后的卡尔曼滤波算法能够有效减小运动加速度对姿态解算的影响,姿态角的均方根误差相对于传统的姿态参考系统降低约40%。
[Abstract]:In view of the traditional attitude reference system attitude solution is easy to be disturbed by the acceleration of the carrier motion, which leads to the system precision become lower, the stability of the system becomes poor, and so on. An improved Kalman filter algorithm is proposed, which establishes a quaternion based mathematical model for attitude calculation of inertial system, and adjusts the measurement noise variance of Kalman filter in time according to the acceleration of carrier motion. In order to reduce the influence of motion acceleration on attitude angle resolution accuracy during Kalman filtering, the MEMS three-axis gyroscope, accelerometer and magnetoresistive sensor are used to measure the carrier in the elevator lifting process. The results show that the improved Kalman filter algorithm can effectively reduce the effect of motion acceleration on attitude resolution, and the RMS error of attitude angle is about 40% lower than that of traditional attitude reference system.
【作者单位】：西南交通大学机械工程学院;
【分类号】：TP212;TN713

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