To solve the problems that the MEMS gyroscope is greatly affected by random error and filtering is needed, and the random error model established by time series analysis method cannot be directly applied to the dynamic filtering, a random error dynamic filtering method based on angular velocity estimation model is proposed.Firstly, analysis is made to the MEMS gyroscope random error and the model is established by using time series analysis method.Then, the angular velocity estimation hypothesis model is established as a three-dimensional linear model, which is combined with gyroscope random error model to form a dynamic filtering model.Finally, strong tracking Kalman filter method is used directly to estimate the angular velocity value for realizing random error filtering, and experimental verification is made.The results show that:The angular velocity value estimation accuracy of this filtering method is high under both static and dynamic conditions, and it can effectively reduce the random error of MEMS gyroscope and improve its accuracy.