Virtual Precession Self-Calibration Method for Hemispherical Resonator Gyro Based on Sinusoidal Injection

Coriolis Vibratory Gyros commonly employ virtual precession for the online calibration of assembly, damping, and angular errors. However, the impact of precession stability on gyro performance is often overlooked in the calibration process. This article presents a novel method for virtual precession self-calibration from the signal processing perspective. Initially, a comprehensive error model for virtual precession is established, elucidating the influencing mechanism of resonant frequency and high-voltage changes on the precession rate. Subsequently, a sinusoidal signal is introduced into the virtual precession rate to separate the precession error from the resonator structure error. Finally, the dynamic recursive least squares (DRLS) algorithm is employed for real-time characterization of the precession error, and the identification results are fed back to the control system for self-calibration of the virtual precession. The experimental results reveal that following self-calibration, the gyro’s stabilization time in a variable temperature environment is reduced significantly from 50 to 10 min. Additionally, the rate error diminishes from $4.3 \times 10^{-3}$ °/s to $1.6 \times 10^{-4}$ °/s, and the rate stability at different temperatures decreases from 6.35°/h to 0.24°/h. This method is not constrained by the gyro’s structure and environment, making it applicable to large-scale engineering applications.