An Alternative Methodology for Fiber Optic Gyroscope Calibration

The objective of this paper is to present an alternative calibration technique for a Fiber Optic Gyroscope (FOG). Emphasis is placed on the use of neural networks to aid in the calibration process. The main objective is to reduce the cost of the calibration process by reducing the required time on a 3-axis rotation table and the amount of engineering time required to process the data. An innovative approach is also presented where the calibration is performed on the level of the sensor (gyro) instead of being performed on the system (Inertial Measurement Unit (IMU)) level. The new calibration methodology is presented and simulation results supporting the new concept is presented.

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