A novel hybrid algorithm of split-radix fast Fourier transform and unscented Kalman filter for navigation information estimation

To improve the state estimation accuracy and reduce the computational time for navigation system applied to underwater glider. This paper proposes a novel hybrid algorithm of split-radix fast Fourier transform and unscented Kalman filter (SRFU) for navigation information estimation. The SRFU algorithm makes better use of high effective computation for split-radix fast Fourier transform and state estimation for UKF in the nonlinear system. The proposed algorithm is implemented in the navigation system designed by our lab and meanwhile compared with other algorithms. The experiment results show that the proposed algorithm outperforms other algorithms and has the better advantages in terms of estimation accuracy and computational cost.