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

Autor:	Xiyuan Chen, Zhikai Zhou, Haoqian Huang, Caiping Lv
Rok vydání:	2015
Předmět:	Engineering business.industry Computation Fast Fourier transform Navigation system Kalman filter Hybrid algorithm Computer Science::Robotics Extended Kalman filter Control theory Fast Kalman filter Unscented transform business Algorithm
Zdroj:	2015 IEEE Metrology for Aerospace (MetroAeroSpace).
DOI:	10.1109/metroaerospace.2015.7180633
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::dd984755eb503c590724111f1b41df47 https://doi.org/10.1109/metroaerospace.2015.7180633 Zobrazit plný text záznamu