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Volume 42 Issue 7
Jul.  2016
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Journal of Beijing University of Aeronautics and Astronautics  > 2016  >  42(7): 1352-1360.
WANG Lixin, LI Can, JIANG Zhou, et al. Design of dynamic total variance and its fast algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(7): 1352-1360. doi: 10.13700/j.bh.1001-5965.2015.0488(in Chinese)
Citation: WANG Lixin, LI Can, JIANG Zhou, et al. Design of dynamic total variance and its fast algorithm[J]. Journal of Beijing University of Aeronautics and Astronautics, 2016, 42(7): 1352-1360. doi: 10.13700/j.bh.1001-5965.2015.0488(in Chinese)
shu

Design of dynamic total variance and its fast algorithm

doi: 10.13700/j.bh.1001-5965.2015.0488
  • 1.

    Department of Control Science and Engineering, The Second Artillery Engineering University, Xi'an 710025, China

  • 2. School of Energy and Power Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

  • Received Date: 20 Jul 2015
  • Publish Date: 20 Jul 2016
    Abstract
  • There exist two shortcomings in Allan variance approach when it is used to analyze random error. First, the vibration of estimated value is large in long-term correlation. Second it can't follow the dynamic change of signal.This paper integrates the thought and advantage of total variance and dynamic allan variance, and proposes the dynamic total variance approach. Firstly, original data is truncated by window function. Secondly, we continue the data in the window. Then the data after continuation is analyzed by total variance, so that local random characteristic is acquired. With the window sliding, the change of random characteristic of original signal with time is obtained. Through verification, the dynamic total variance can solve the two shortcomings of Allan variance approach. Eventually, linear vibration trial of hemispherical resonator gyro(HRG) is designed to clarify this new algorithm, which indicates that dynamic total variance possesses advantages in analysis accuracy and data quantity that it used. However, this new algorithm has the problem of excessive calculation and low speed of analysis, so we derive recursive formula of it, based on which fast algorithm is provided.

     

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