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Fiber-optic gyro strapdown inertial navigation system is typically physically separated from the log giving an aiding velocity. This results in a velocity difference under angular motions, otherwise known as the outer lever arm effect. The mathematical relationship between the velocity difference and the outer lever arm is derived, and the effect of the outer lever arm on angular velocity compensation and harmful acceleration compensation is analyzed using the structure of in-motion gyrocompass alignment. Based on this analysis, a method for outer lever arm correction is given to counteract the outer lever arm effect on the performance of the alignment. Simulation and trial tests are then used to verify the analysis results. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Conventional strapdown gyrocompass alignment methods are based on the assumption that the fiber-optic-gyro inertial navigation system has a small azimuth misalignment angle. A large azimuth misalignment angle would lead to an extension of the alignment duration. A time-varying gyrocompass alignment method to solve this problem is provided. An appropriate parameter setting is given for the gyrocompass alignment with a large misalignment angle. Also, a proper protocol for a parametric switch is derived. Simulation and trail results show that the proposed method has better alignment performance than conventional ones, as the system has large misalignment angles. [ABSTRACT FROM AUTHOR]

This paper aims to propose a new strapdown fiber optic gyrocompass (strapdown FOGC) using adaptive network-based fuzzy inference system (ANFIS). The strapdown FOGC is based on the principle of strapdown inertial navigation system and utilizes electromagnetic log (EM log) and damping equalizer to bound oscillatory errors existing in attitude and heading. As the introduction of damping technique, extra errors are aroused by EM log errors. To decrease the extra errors, ANFIS is utilized to adjust the damping ratio automatically in terms of the ship maneuver conditions. The simulation and trial results indicate that, compared with the conventional gyrocompass scheme, the proposed one can reduce the attitude and heading errors and improve the system performance effectively. [ABSTRACT FROM AUTHOR]