Application of improved UKF algorithm in initial alignment of SINS

In order to improve the initial alignment accuracy and convergence rate of the SINS system, proposed the improved UKF algorithm (AUKF) based on the Unscented Kalman Filter (UKF). Noise statistical characteristics are mostly unknown in real systems, when it was effected by the initial value errors and dynamic model errors, AUKF algorithm can real-time adjust the covariance of the state vector and observation vector, and balance the right ratio of the state information and observation information in the filter results, thereby improving the system performance. The experimental results show: The Improved UKF Algorithm enhances the convergence speed and alignment accuracy effectively.