Since a good knowledge of MEMS gyro stochastic errors is important and critical to MEMS INS/GPS integration system. Therefore, the stochastic errors of MEMS gyro should be accurately modeled and identified. The Allan variance method is IEEE standard method in the filed of analysis stochastic errors of gyro. This kind of method can fully characterize the random character of stochastic errors. However, it requires a large amount of data to be stored, resulting in large offline computational burden. Moreover, it has a painful procedure of drawing slope lines for estimation. To overcome the barriers, a simple linear state-space model was established for MEMS gyro. Then, a recursive EM algorithm was implemented to estimate the stochastic errors of MEMS gyro in real time. The experimental results of ADIS16405 IMU show that the real-time estimations of proposed approach are well within the error limits of Allan variance method. Moreover, the proposed method effectively avoids the storage of data.
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