Composite Compensation Method for Scale-Factor Nonlinearity in MEMS Gyroscopes Based on Initial Calibration

With the advancement of error correction techniques such as quadrature suppression and mode matching, the bias stability and overall accuracy of MEMS gyroscopes have been greatly improved. However, scale-factor nonlinearity often being underestimated has emerged as a critical barrier to further performance enhancement in high-precision MEMS gyroscopes. This study investigates the mechanism of scale-factor nonlinearity in closed-loop MEMS gyroscopes and introduces the concept of scale-factor repeatability error. A constraint relationship between scale-factor nonlinearity and repeatability is analytically established. Based on this insight, a composite compensation method incorporating initial calibration is proposed to enhance scale-factor linearity. By improving repeatability, the effectiveness and accuracy of polynomial fitting-based compensation are significantly improved. Experimental results show that the proposed method reduces the scale-factor nonlinearity error from 2232.039 ppm to 99.085 ppm, achieving a 22.5-fold improvement. The proposed method is also applicable to other MEMS gyroscopes with similar architectures and control strategies.