Design of complementary filter for high-fidelity attitude estimation based on sensor dynamics compensation with decoupled properties

A high-fidelity attitude estimation technique for wide and irregular movements is proposed, in which heterogeneous inertial sensors are combined in complementary way. Although the working frequency ranges of each sensor are not necessarily complementary, inverse sensor models are utilized in order to restore the original movements. In the case of 3D rotation, the sensor dynamics displays a highly nonlinear property. Even if it is approximated by a linear system, the inverse model of a sensor tends to be non-proper and unstable. An idea is to decouple it into the dynamics compensation part approximated by a linear transfer function and the strictly nonlinear coordinate transformation part. Bandpass filters inserted before the coordinate transformation guarantee that the total transfer function becomes proper and stable. Particularly, the differential operator of a high-pass filter cancels the integral operator included in the dynamics compensation of the rate gyroscope, which causes instability. The proposed method is more beneficial than Kalman filter in terms of the implementation since it facilitates a systematic design of the filter.