Performance evaluation of FOGs based on improved Bayes method

Mian Ye; Jinchen Zhao; Tao Wang

doi:10.1117/12.2646851

7 September 2022 Performance evaluation of FOGs based on improved Bayes method

Mian Ye, Jinchen Zhao, Tao Wang

Author Affiliations +

Proceedings Volume 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022); 123293R (2022) https://doi.org/10.1117/12.2646851
Event: Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 2022, Changsha, China

Abstract

How to conduct FOGs (fiber optic gyros) performance evaluation under small samples condition has been the focus of FOGs research. In this paper, an improved performance evaluation method of FOGs based on modified Bayes is proposed, which fuses the random weighting method to determine the priori distribution, and combines the likelihood function established by small sample test data to evaluate the performance of FOGs. The simulation results show that the proposed method substantially reduces the length of the confidence interval without reducing the confidence, improves the accuracy of the estimation results, and has important theoretical significance and reference value for solving the FOG performance evaluation problem under small samples.

Citation Download Citation

Mian Ye, Jinchen Zhao, and Tao Wang "Performance evaluation of FOGs based on improved Bayes method", Proc. SPIE 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 123293R (7 September 2022); https://doi.org/10.1117/12.2646851

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