Abstract

Due to the temperature delay effect, the coefficients of the traditional ring laser gyroscope's (RLG) bias temperature model usually change with environmental temperature. In order to improve the applicability of the temperature model in complex temperature-varying environments, a modified RLG bias modeling method based on the temperature delay effect is proposed. The time series model (TSM), whose coefficients are independent of the environmental temperature variation, is established through theoretical analysis according to the temperature delay effect. The forecasting accuracy of the proposed method is compared with the conventional stepwise regression model (SRM) when both the temperature and temperature-varying rate exceed their boundaries. The experimental results indicate that the proposed TSM can overcome the defect that the compensation accuracy will decline or even diverge when outside the boundaries of temperature and temperature-varying rate. Therefore, the TSM is more suitable for the RLG bias temperature modeling in complex temperature-varying environments.

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