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The Fast algorithm of the dynamic Allan variance for gyroscopes

机译:陀螺仪动态艾伦方差的快速算法

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摘要

The dynamic Allan variance (DAVAR) [1] is a useful tool to track non-stationaries in the behavior of gyroscopes. It allows us to diagnose whether the stability of gyroscopes is changing with time. Unfortunately, with the length of the analyzed time series increasing, the computational time of the DAVAR grows very quickly. Consequently, it costs huge time to deal with the data. In this article, a Fast algorithm of the DAVAR for gyroscopes is developed. In order to verify its validity, three sets of simulation data are characterized by the Fast algorithm and the classical one. The Fast DAVAR could reduce the computational time dramatically when the long time series is analyzed. Furthermore, a vibration experiment with fiber optic gyroscopes has been implemented to validate the good performance of the Fast algorithm. Compared with the classical one, the Fast algorithm of the DAVAR shortens the computation time 6 times. In conclusion, the Fast algorithm of the DAVAR guarantees a dramatic reduction of the computational time and outperforms the classical DAVAR. (C) 2015 Elsevier GmbH. All rights reserved.
机译:动态艾伦方差(DAVAR)[1]是跟踪陀螺仪行为中的非平稳性的有用工具。它使我们能够诊断陀螺仪的稳定性是否随时间变化。不幸的是,随着所分析时间序列的长度增加,DAVAR的计算时间非常快地增长。因此,花费大量时间来处理数据。在本文中,开发了用于陀螺仪的DAVAR的快速算法。为了验证其有效性,使用Fast算法和经典算法对三组仿真数据进行了表征。当分析长时间序列时,快速DAVAR可以大大减少计算时间。此外,已经实施了光纤陀螺仪的振动实验,以验证Fast算法的良好性能。与经典算法相比,DAVAR的Fast算法将计算时间缩短了6倍。总之,DAVAR的快速算法可确保显着减少计算时间,并且性能优于传统的DAVAR。 (C)2015 Elsevier GmbH。版权所有。

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