Abstract
In order to solve the problem of low precision and large cumulative error of MEMS gyroscope in MTi-28A53G35, the random drift model of the MEMS gyroscope is studied. In this paper, the ARIMA model is used to model the measured data noise of the preprocessed MEMS gyroscope, and then the specific method of reducing the drift error based on the Kalman filtering method based on time series model is discussed in detail. The error compensation results of the measured data of the MEMS gyroscope show that the proposed filtering method can effectively reduce the drift error and improve the accuracy of the MEMS gyroscope in the actual system.
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