Abstract

We present a laser-driven interferometric fiber optic gyroscope (IFOG) with polarization self-compensation to achieve high scale-factor stability, sensitivity, and long-term stability. Coherent light with 200kHz linewidth is employed to keep the scale factor stable. The optical scheme ensures polarization reciprocity as well as the optimal working point for good sensitivity. Furthermore, a hybrid machine learning loop (MLL) method, combining the advantages of PID fast response and artificial neural network (ANN) dynamic search, can control a liquid crystal rotator (LCR) to dynamically compensate for slow drift induced by polarization coupling. In open environment, when the sensitivity is 0.005∘/h, the bias instability (BI) is significantly optimized from 0.6723°/h at 60s (PID) to 0.3869°/h at 200s (MLL), which is close to the Sagnac interferometric limit (SIL). Such IFOG can meet the real-time and robust requirements for inertial navigation systems in long-term measurement.

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