Concentrating on the issue that the existence of wind has an effect on the attitude estimation of unmanned aerial vehicle (UAV) and thereafter degrades the controllability of the UAV, based on the extended Kalman filter (EKF), an approach of UAV attitude estimation is proposed in the presence of wind interference. Firstly, attitude quaternion and drift bias of gyroscope are selected to construct the state vector, and the state equation is established based on the kinematics model of gyroscope. After that, observation equation can be obtained via using the measurement of accelerometer, magnetometer, and airspeed tube. In what follows, the EKF update equation is exploited to determine the UAV attitude. As compared to the traditional EKF and unscented Kalman filter, experimental results show that the proposed algorithm can depress the divergence of attitude angle obviously, upgrade the attitude measurement accuracy considerably, and lower the attitude angle error significantly.

中文翻译：

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存在风扰的无人机姿态测量

针对风的存在对无人机姿态估计产生影响，进而降低无人机可控性的问题，基于扩展卡尔曼滤波器(EKF)，提出了一种无人机姿态估计方法。在存在风干扰的情况下。首先选取陀螺仪的姿态四元数和漂移偏差构造状态向量，并基于陀螺仪的运动学模型建立状态方程。之后，利用加速度计、磁力计和空速管的测量可以得到观测方程。在下文中，利用 EKF 更新方程来确定无人机姿态。与传统的 EKF 和无味卡尔曼滤波器相比，