Title :
Federated filtering algorithm based on fuzzy adaptive UKF for marine SINS/GPS/DVL integrated system
Author :
Zhou, Benchuan ; Cheng, Xianghong
Author_Institution :
Sch. of Instrum. Sci. & Eng., Southeast Univ., Nanjing, China
Abstract :
For marine SINS/GPS/DVL integrated navigation system, a new federated filtering algorithm based on fuzzy adaptive unscented Kalman filter is presented in order to satisfy the precision and fault-tolerance demands. The algorithm uses unscented Kalman filter (UKF) to estimate the nonlinear system states, as well as using fuzzy inference system (FIS) to amend measurement noise adaptively. The simulation in marine SINS/GPS/DVL integrated system illustrated that, compared with the traditional federated Kalman filtering algorithm, the algorithm in this paper can improve the navigation precision and fault-tolerant capability effectively, the velocity-error decreased from 0.14m/s to 0.06m/s.
Keywords :
Global Positioning System; Kalman filters; filtering theory; fuzzy set theory; inertial navigation; inference mechanisms; marine systems; fault-tolerant capability; federated filtering algorithm; fuzzy adaptive UKF; fuzzy inference system; marine SINS-GPS-DVL integrated navigation system; nonlinear system states; unscented Kalman filter; Fault tolerant systems; Filtering algorithms; Fuzzy systems; Global Positioning System; Inference algorithms; Navigation; Noise measurement; Nonlinear systems; Silicon compounds; State estimation; Federated filter; Fuzzy inference system; Integrated navigation; Unscented Kalman filter;
Conference_Titel :
Control and Decision Conference (CCDC), 2010 Chinese
Conference_Location :
Xuzhou
Print_ISBN :
978-1-4244-5181-4
Electronic_ISBN :
978-1-4244-5182-1
DOI :
10.1109/CCDC.2010.5498869