Abstract
Random drift is a significant index that can affect the precision of MEMS gyroscope. It is one of the important techniques to decrease the random drift error in improving the precision of MEMS gyro. According to analyzing the principle of traditional Wavelet Transform and Stationary Wavelet Transform, Stationary Wavelet Transform (SWT) is adopted to de-noise the signal of MEMS gyro. Due to SWT’s time-invariant, the Gibbs phenomenon is decreased. SWT with adaptive threshold is adopted to analyze the actual dynamic MEMS gyroscope data. The experimental results show that this presented method is better than traditional wavelet threshold de-noising methods. It can effectively restrain the noise in high frequency and improve the drift error of MEMS gyro.
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