Systems Engineering and Electronics ›› 2025, Vol. 47 ›› Issue (10): 3446-3454.doi: 10.12305/j.issn.1001-506X.2025.10.28

• Guidance, Navigation and Control • Previous Articles    

Temperature error compensation method for fiber-optic gyroscope based on thermal diffusion theory

Yunhao ZHANG1,2, Zhaofa ZHOU1,2,*, Zhili ZHANG1,2, Hongcai LI1,2, Zhe LIANG1,2, Jin LIU1,2   

  1. 1. School of Missile Engineering,Rocket Force University of Engineering,Xi’an 710025,China
    2. State Key Discipline Laboratory of Armament Launch Theory and Technology,Rocket Force University of Engineering,Xi’an 710025,China
  • Received:2025-01-06 Online:2025-10-25 Published:2025-10-23
  • Contact: Zhaofa ZHOU

Abstract:

A thermal induced error compensation method for fiber-optic gyroscopes based on thermal diffusion is proposed to address the problem of one-sided compensation for temperature errors caused by a single temperature data. Firstly, a prediction model for the temperature at any point along the axial direction of the fiber optic ring is established based on the principle of thermal diffusion. Then, based on this model, the polynomial and back propagation (BP) neural network temperature compensation models are optimized separately. Finally, under the conditions of full temperature testing, combined with finite element analysis, the accuracy of the temperature prediction model is verified. The optimized compensation model is then used to compensate for the output bias of the multiple fiber-optic gyroscopes. The experimental results show that the optimized polynomial compensation model can improve the compensation accuracy by 67.4% compared to the traditional compensation model, and the optimized BP neural network compensation model can improve the compensation accuracy by up to 90.0% compared to the original data. Compared with the single temperature data compensation, the proposed method effectively improves the output accuracy of the fiber-optic gyroscope.

Key words: fiber-optic gyroscope, zero bias stability, temperature compensation, polynomial fitting, back propagation (BP) neural network

CLC Number: 

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