Abstract:Stable and accurate attitude estimation is the key to the autonomous control of unmanned aerial vehicle (UAV). The attitude heading reference system(AHRS), using the micro electronic mechanical system inertial measurement unit(MEMSIMU) as the measurement sensors, is an indispensable system forUAV′sattitude estimation. Aiming at the problem oflowprecision usingextendedKalmanfilter(EKF)andunscentedKalmanfilter(UKF) caused bythe nonlinearattitude model,anattitudeheadingreference algorithm basedon nonlinearsliding modefilter is proposed. Meanwhile, aiming at the problem that the traditional attitude heading reference algorithm cannot estimate the motion acceleration, an estimation algorithm of motion acceleration using Kalman Filter is proposed based on the motion characteristics of micro UAV, which realizes the online estimation of motion acceleration. The carbased and flightbased test show that the algorithm proposed in this paper can accurately estimate the carrier′s motion attitude and motion acceleration without GPS. The accuracy of acceleration reaches 015 m/s2, and the accuracy of attitude reaches 1°.