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

Area of Science:

• * Engineering
• * Sensor Technology

Background:

• * Micro-electro-mechanical systems (MEMS) gyroscopes have seen improved bias stability and accuracy due to error correction techniques.
• * Scale-factor nonlinearity remains a significant limitation for high-precision MEMS gyroscopes.
• * Underestimation of scale-factor nonlinearity hinders further performance enhancements.

Purpose of the Study:

• * To investigate the mechanism of scale-factor nonlinearity in closed-loop MEMS gyroscopes.
• * To introduce and analyze the concept of scale-factor repeatability error.
• * To propose a composite compensation method for enhancing scale-factor linearity.

Main Methods:

• * Analytical establishment of a constraint relationship between scale-factor nonlinearity and repeatability.
• * Development of a composite compensation strategy integrating initial calibration.
• * Utilizing improved repeatability to enhance polynomial fitting-based compensation.

Main Results:

• * A significant reduction in scale-factor nonlinearity error from 2232.039 ppm to 99.085 ppm (a 22.5-fold improvement).
• * Demonstrated enhancement in the effectiveness and accuracy of compensation methods through improved repeatability.
• * Validation of the proposed method's applicability to similar MEMS gyroscope architectures.

Conclusions:

• * The proposed composite compensation method effectively addresses scale-factor nonlinearity in MEMS gyroscopes.
• * Improving scale-factor repeatability is crucial for accurate nonlinearity compensation.
• * The method offers a viable solution for enhancing the performance of high-precision MEMS gyroscopes.