A New Anti-interference Fitering Algorithm for Quad Rotor UAV
Erdong Shi, Jiakang Xu, Xiao Bo Yang, Chensen Tang, Pengyi Zhang, Dehua Zhang, Chunbin Qin · 2021
In recent years, quad rotor Unmanned Aerial Vehicle (UAV) are now used in a broad range of applications. However, due to the interference of White Gaussian Noise(WGN) in the attitude detection data of the aircraft, the stability of the aircraft is poor. These shortcomings are sometimes fatal to UAV. Aiming at the uncertainty of UAV in the course of flight attitude adjustment due to the noise interference of the data obtained by the controller of the quad rotor UAV, a new anti-interference filtering algorithm based on Unscented Kalman Filter(UKF) is designed. The algorithm adopts Kalman linear filtering framework, and uses Unscented Transform(UT) to deal with the nonlinear transfer problems of mean value and covariance. Compared with the traditional Kalman Filter and Extended Kalman Filter(EKF), the simulation results show that the proposed UKF algorithm can effectively reduce the output noise of the control system and have marked improvements in the control performance.