基于EKF的小型涵道式无人机航姿系统算法研究

针对小型涵道式无人机，设计了一种基于扩展Kalman滤波的航姿估计算法。采用四元数作为状态变量，利用陀螺仪的输出构成状态方程，通过加速度计与磁阻传感器构造观测方程来进行扩展Kalman滤波解算。相对于通常的航姿估计算法，这种算法减少了运算量，更适合于基于嵌入式微处理器的航姿估计。实验结果表明这种算法有效的抑制了航姿系统的各种噪声与干扰，同时保证了姿态输出的精度与实时性，可以为小型无人机提供准确的航姿信息。

AHRS Algorithm Research for Micro Ducted Fan UAVs Based on EKF

This paper proposes an extended Kalman filter to estimate the heading and attitude information of the small UAV. In the filter, the quaternion is chosen as state variables, gyros are used to update the stats variables, and accelerators and magnetic sensors are combined to establish measurement equation. In comparison with the traditional attitude estimation method, this algorithm can greatly reduce computational complexity and is more suitable to attitude estimation based on embedded microprocessor. Experiment results show that the algorithm can restrain the error and disturbance of heading and attitude system effectively, and the attitude output is stable and accurate, and this method is suitable for small UAV attitude estimation.