In order to reduce the low-frequency noise in the output signal of MEMS accelerometer and improve the signal accuracy,a filtering method based on EMD and fractal Gaussian noise is proposed.The yaw rate signal output by the accelerometer uses the sliding window method to estimate Hurst parameters from the window data using the aggregate variance method,and obtains the IMF components and residuals of each layer through the EMD decomposition window data,calculates the window threshold and conducts threshold processing selection,gradually processes the sliding window data,integrates the processed IMF components and residuals,and obtains the filtered signal data.The feasibility of the filtering method to improve the precision of signal noise is proved by simulation experiment and real vehicle data verification.
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