Title :
Application of Fuzzy Federal Kalman Filtering in the Airport Automatic Docking Guidance System
Author :
Hu, Dandan ; Gao, Qingji ; Han, Guangdong
Author_Institution :
Dept. of Aeronaut. Autom., Civil Aviation Univ. of China, Tianjin
Abstract :
A novel method based on fuzzy federal Kalman filtering is presented, which is mainly used to improve the reliability of the airport automatic docking guidance system when measure values of sensors are fluctuated. If the measure values are fluctuated, the state vector covariance of each local filtering is modified by using the fuzzy inference system (FIS) to modify the weight of each fusion data online in main filtering, accordingly the disturbance of the fluctuation data is reduced. Experiment results proved that the algorithm was feasible to improve the reliability of the system.
Keywords :
Kalman filters; aircraft landing guidance; airports; fuzzy reasoning; sensor fusion; airport automatic docking guidance system; data fusion; fuzzy federal Kalman filtering; fuzzy inference system; state vector covariance; Aircraft; Airports; Automation; Fuzzy systems; Information filtering; Information filters; Kalman filters; Laser fusion; Sensor fusion; Sensor systems; Docking Guidance System; FIS; Federal Kalman Filtering; Fusion;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4593493
