【摘要】 针对小型四旋翼飞行器航姿测量系统中MEMS器件精度低、易发散等问题,提出一种新的数据融合方法,对航姿测量系统中陀螺仪、加速度计和电子罗盘的输出数据进行融合。利用MEMS惯性测量元件搭建了一个低成本航姿测量系统,分析了姿态解算的过程和难点,采用基于梯度下降的姿态融合算法,对四元数更新方程进行了补偿。实验结果表明:与目前常用的卡尔曼滤波算法相比,基于梯度下降的数据融合算法能显著降低对处理器速度和精度的要求,能有效融合航姿测量单元的传感器数据,提高小型四旋翼飞行器的姿态测量精度。更多还原

【Abstract】 For overcoming low precision and easy to divergence of MEMS inertial measurement sensors of small size quad-rotor aircraft attitude measurement,a new data fusion method is designed to fuse the information from gyroscope,accelerometer and magnetometer.Use the MEMS inertial measurement components to construct a low-cost attitude heading measurement system,analyze the attitude estimation process and difficulties.Based on gradient descent,use attitude fusion algorithm to compensate quaternion updating equation.Experimental results show that the data fusion method based on the gradient descent algorithm is better than the Kalman filtering algorithm,and can significantly reduce the requirements of precision and speed for the processor,effectively fuse sensor data and improve the accuracy of attitude estimation of the small quad-rotor.更多还原