A multiple regression based method for indirect compensation of hemispherical resonator gyro temperature error

In order to improve the measuring accuracy of the Hemispherical Resonator Gyro under variable temperature, aiming at the problem of "external temperature is unavailable and internal temperature is unmeasurable," a multiple regression based method is proposed for compensating temperature error in the gyro. The relationship between the internal temperature and the resonant frequency of the gyro is analyzed theoretically. According to a constant temperature experiment, a linear relationship between them is derived based on the least square method. The analysis of a temperature-rising experiment shows that the correlation of the gyro output with the internal temperature is much higher than that with the external temperature. Therefore, taking the resonant frequency as an independent variable, a multiple regression model is established for compensating the temperature error. The compensation effect of the model is verified by temperature-rising and temperature-dropping experiments, which show that the output sequence before compensation is not stable, while it is stable after compensation. After compensation, the drift of the gyro decreases by 62.76% and 48.48%, respectively, and its measuring accuracy becomes equivalent to that at the constant temperature. The experimental results verify the feasibility and effectiveness of the model developed for indirect compensation of temperature error.