A novel IFOG Allan variance coefficients real-time detection method with temperature variation in moorage

The interferometric fiber optic gyro (IFOG) that is inside the gyrocompass has been gradually equipped on the marine vessel and the vessel's swing is sensed by IFOG. This will affect the detection of Allan variance coefficients of IFOG while the vessel is in moorage especially in temperature variation conditions. However, the standard IFOG Allan variance noise analysis method is computationally expensive and requires massive data storage which is inappropriate for Allan variance coefficients real-time detection. In addition, for long-voyage and long-endurance requirements of the vessel in the marine environments, the ambient temperature variation causes errors that will degenerate IFOG accuracy. The vessel needs more independence including the fault diagnosis system and reconfiguration of the IFOG gyrocompass. To meet the marine vessel autonomy need, we propose a method for Allan variance coefficients detection including rate ramp R, rate stochastic walk K, bias instability B, angular stochastic walk N and quantization noise Q. In the study, we first eliminate the angular increments of vessel attitude by gravity in inertial frame in the moorage condition, and then realize the Allan variance coefficients real-time detection by adopting nonlinear adaptive Kalman filter with proposed state-space model. Simulations show that the proposed method potentially could implement the Allan variance coefficients’ real-time detection, and estimate the coefficients’ temperature variation effectively and correctly.