A Fast Alignment Algorithm Based on Adaptive Quaternion Kalman Filter

The initial alignment is a key technology for strapdown inertial navigation system (SINS), because the performance of the SINS is largely decided by the accuracy and rapidity of the alignment process. In this paper, a novel alignment method is developed by combining the quaternion Kalman filter with optimization-based alignment idea. The process model and measurement model of the proposed alignment method are constructed based on the properties of quaternion. Since the correlation measurement noise in the measurement formula, the adaptive filter of the quaternion Kalman filter combined with innovation-based adaptive estimation is developed, which calculate the filter gain matrix by the innovation covariance on-line. The simulation and experimental results demonstrate that the proposed alignment method has more accurate alignment results compared with the existing alignment methods.