Pose Estimation with Adaptive Complementary Filtering Based on Decision Tree
In order to solve the problem of the attitude estimation accuracy decline of the inertial sensor in the environment of magnet-ic field interference and large acceleration interference,a complementary filter attitude estimation method based on decision tree adaptive was proposed.Aiming at the zero-degree offset characteristic of the gyroscope,it performed zero-degree offset processing.The processed angular velocity data and acceleration data constituted a static detection unit,which realized accurate classification of static and dynamic situations.In the dynamic situation,the decision tree composed of acceleration data and magnetic field data can automatically adjust the system error gain by analyzing the degree of external interference,so as to achieved the purpose of anti-interference and effectively im-prove the accuracy of attitude estimation.The experimental results show that the attitude estimation is not affected by the magnetic field in the static state,and can effectively avoid the magnetic field interference and the large acceleration interference in the dynamic state.
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