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Comparison of Random Error Analysis Methods for Fiber Optic Gyro Based on Allan Variance
Science Discovery
Volume 5, Issue 5, October 2017, Pages: 375-379
Received: Sep. 12, 2017; Published: Sep. 14, 2017
Views 1465      Downloads 82
Authors
Du Xiao Jing, School of Aerospace Engineering, Beijing Institute of Technology, Beijing, China
Zeng Chun, School of Aerospace Engineering, Beijing Institute of Technology, Beijing, China
Li Huai Jian, School of Aerospace Engineering, Beijing Institute of Technology, Beijing, China
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Abstract
It is an effective method to improve the performance of inertial instrument and the accuracy of inertial navigation system by analyzing the random drift of FOG (Fiber Optic Gyro). Allan variance FOG random error analysis method, through analyze and compare Allan variance of the original data, you can correctly evaluate the gyroscope performance indicators. In this paper, we introduce the several different random error analysis method of FOG based on Allan variance, and analyze the different Allan variance of the same group by writing the program, and more, compare the three common quantities of the FOG random error model. The results show that the modified Allan variance method obviously takes a lot of time in the processing time, but the "2k" Allan variance law is calculated more quickly. In the processing effect, the modified Allan variance method can get better calculation results. In general, the "k" Allan variance method and the smooth Allan variance method are more balanced in the computational time and the computational effect. Several Allan variance methods can effectively identify the random error components of FOG, in the actual situation, according to different conditions of use to choose the appropriate treatment.
Keywords
Fiber Optic Gyro, Random Error Model, Allan Variance Eethod
To cite this article
Du Xiao Jing, Zeng Chun, Li Huai Jian, Comparison of Random Error Analysis Methods for Fiber Optic Gyro Based on Allan Variance, Science Discovery. Vol. 5, No. 5, 2017, pp. 375-379. doi: 10.11648/j.sd.20170505.22
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