In order to realize the self-alignment function of the low-cost Micro Inertial Measurement Unit (MIMU) and improve the self-alignment accuracy, this paper proposes a method of moving MIMU self-alignment assisted by GPS single antenna based on Kalman Cascade Filtering (KCF).Firstly, the Modified Ensemble Empirical Mode Decomposition (MEEMD) is performed on the random error of the velocity vector measured by the GPS single antenna, and after signal reconstruction, Kalman filtering is used for denoising calculation to obtain the heading angle measurement.Secondly, the state equation of the system is established by taking the attitude angles of the base and gyroscope constant drift as the state variables, and the observation equation of the system is established by fusing the accelerometer and GPS single antenna measurement information.Then, the Adaptive Unscented Kalman Filter (AUKF) is used for information fusion, and the optimal estimation of the attitude angles of the base is realized.After simulation verification and comparison, it is proved that the proposed method effectively improves the self-alignment accuracy.The simulation results validate the superiority of the proposed algorithm in MIMU self-alignment assisted by GPS single antenna.