Abstract
In view that traditional dynamic Allan variance (DAVAR) method is difficult to make a good balance between dynamic tracking capabilities and the confidence of the estimation. And the reason is the use of a rectangular window with the fixed window length to intercept the original signal. So an improved dynamic Allan variance method was proposed. Compared with the traditional Allan variance method, this method can adjust the window length of the rectangular window adaptively. The data in the beginning and terminal interval was extended with the inverted mirror extension method to improve the utilization rate of the interval data. And the sliding kurtosis contribution coefficient and kurtosis were introduced to adjust the length of the rectangular window by sensing the content of shock signal in terminal interval. The method analyzed the window length change factor in different stable conditions and adjusted the rectangular window’s window length according to the kurtosis, sliding kurtosis contribution coefficient. The test results show that the more the kurtosis stability threshold was close to 3, the stronger the dynamic tracking ability of DAVAR would be. But the kurtosis stability threshold was too close to 3, there was a misjudgement in kurtosis analysis of signal stability, resulting in distortion of DAVAR analysis results. When using the improved DAVAR method, the kurtosis stability threshold can be close to 3 to improve the tracking ability and the estimation confidence in stable interval. Therefore, it solved the problem that the dynamic Allan variance tracking ability and confidence level were difficult to take into account, and also solved the problem of misjudgement in the stability analysis of kurtosis.
Highlights
Micro electromechanical system (MEMS) gyroscope has the advantages of small size, light weight, and low cost [1,2,3,4], which is widely used in various fields of modern navigation
This article elaborates the shortcomings of Allan variance and dynamic Allan variance by using these two methods to analyze the analog MEMS gyro signal
Because the dynamic Allan variance analysis using the rectangular window with a fixed window length to capture the original signal has the disadvantage of power leakage and insensitive tracking of the impact signal
Summary
Micro electromechanical system (MEMS) gyroscope has the advantages of small size, light weight, and low cost [1,2,3,4], which is widely used in various fields of modern navigation. The DAVAR method intercepts the original signal using a fixed length rectangular window which has a defect of power leakage and low confidence in identifying noise. Because the dynamic Allan variance analysis which use the rectangular window with a fixed window length to intercept the original signal has the disadvantage of power leakage and insensitive tracking of the impact components in the signal, so the paper proposes a method which uses sliding kurtosis contribution coefficient to sense the impact component at the end of the intercepted signal, and use the sliding kurtosis contribution coefficient and kurtosis together to control the rectangular window length. It is found that the sliding kurtosis contribution coefficient can sense the content of the impact component at the end of the intercepted signal so that the window length of the rectangular window can be adjusted in time, which enhances the sensitivity of the dynamic Allan variance analysis to the impact signal. The feasibility of the proposed method is verified through the actual measurement and the analysis of MEMS gyroscope signals
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