Attitude Estimation Algorithm for Multi Rotor Aircraft Based on Extended Kalman Filtering

The accuracy of attitude calculation is a prerequisite for achieving stable flight of multi rotor unmanned aerial vehicles. Currently, gyroscopes are commonly used to obtain the attitude angle of aircraft. However, there is a problem of drift in the gyroscope, and the long-term measurement accuracy is poor. Therefore, effective data processing is required for the output data of the gyroscope to obtain reliable and stable attitude angle information. The attitude angle of the carrier can be derived from the output data of the gyroscope through the kinematics differential equation, and its observation equation is nonlinear. The extended Kalman filtering algorithm is a commonly used algorithm for solving nonlinear problems of observation equations. The extended Kalman filter algorithm expands the nonlinear equation in Taylor series, removes the higher order terms above the second order, and linearizes the nonlinear equation. Its advantages are fast operation speed and strong real-time performance. In order to improve the attitude estimation accuracy of the aircraft, this paper uses the extended Kalman filter algorithm to achieve the attitude estimation of the aircraft.