MEMS Gyro Signal Processing based on Improved-Sage-Husa Adaptive Filtering Method

Aiming at the problem that the Micro Electro Mechanical Systems gyro (MEMS gyro) noise in the stable platform control system affects the stability and accuracy of the system, this paper proposes an improved-Sage-Husa adaptive gyro signal filtering algorithm. On the basis of the traditional Sage- Husa adaptive filtering method, the selection method of genetic factors and the suppression method of filtering divergence are improved. First, the ARMA model analysis method is used to construct the state space equation of the MEMS gyro. And then the filter is designed based on the gyro state equation. Finally, simulation experiments prove that the improved-Sage-Husa adaptive filter can obviously suppress the MEMS gyro noise and improve the control accuracy of the stable platform.