A gyro drift error compensation algorithm for a small unmanned aerial vehicle system

To get high precision attitude information, this paper proposes a new time series method to construct the random drift model for the micro electro mechanical sensor gyro. Based on the wavelet multi scale analysis method, the gyro random drift data are decomposed and constructed to a series of scale gyro drift data and models to reduce the predict errors. Moreover, an adaptive Kalman filter algorithm is proposed to compensate for the gyro random drift noise. The effectiveness of the proposed method is proved by a series of experiments.