Aiming at the problem of measurement error caused by signal drift of MEMS acceleration sensor in inertial measurement system, the measured data of MEMS acceleration sensor are analyzed by time series analysis method. After reading the data measured by MEMS acceleration sensor through DSP, the stability is tested by ADF criterion. The sensor data meets the stationary time series conditions. According to the characteristics of autocorrelation function and partial autocorrelation function of sensor data, it is judged that the sequence satisfies AR (P) model. Through AIC criterion for randomness test, time series model identification and parameter estimation, the sensor data is optimized by using AR (1) model. The signal drift AR (1) model of MEMS acceleration sensor is established, and the Kalman filter is designed according to the model. The results show that the zero bias stability of the acceleration sensor before filtering is 0.3032mg, and the zero bias stability of the acceleration sensor after Kalman filtering is 0.0247mg. The measurement stability is effectively improved, and the operation order is low, which can be well applied to the embedded system.