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Self-Adaptive Suppression of the Excess Relative-Intensity-Noise in Fiber Optic Gyroscopes

The excess relative intensity noise (RIN) in the fiber optic gyroscope (FOG) can be suppressed by the balanced intensity addition of the interferometer output signal and the RIN reference. In practice, the suppression effect will be ruined by the mismatching of the intensities at addition induced by...

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Bibliographic Details
Published in:IEEE sensors journal 2023-01, Vol.23 (1), p.1-1
Main Authors: Kong, Linghai, Zhang, Chunxi, Zheng, Yue, Chen, Heyu
Format: Article
Language:English
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Summary:The excess relative intensity noise (RIN) in the fiber optic gyroscope (FOG) can be suppressed by the balanced intensity addition of the interferometer output signal and the RIN reference. In practice, the suppression effect will be ruined by the mismatching of the intensities at addition induced by external environments, resulting in the degradation of the angular-random-walk (ARW) coefficient of the FOG. In this work, we propose a self-adaptive scheme to keep the excess-RIN suppressed at the lowest level. The multiple roles that the modulation depth plays in the loss of the interferometer output signal and the amplitude of each noise component are analyzed, theoretically. Based on this, the modulation depth is designed to be self-adjusted in a closed-loop scheme so as to keep intensity balancing and to maintain the total noise at the lowest level in real time. Experiments show that, under the manually adjusted intensity ratios between the interferometer output signal and the RIN reference from 0.42 to 3.25, the proposed self-adaptive scheme reduces the ARW to 1.24×10 -3 deg/h 1/2 with respect to the conventional case of 2.27×10 -3 deg/h 1/2 . With this technique, the robustness of the excess-RIN suppression is significantly improved without the need of modifying the typical simplest optical configuration or adding any extra device. The lowest ARW for the FOG can be guaranteed in long-term operations and under different environments.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2022.3223701