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

fYear

2008

fDate

25-27 June 2008

Firstpage

3576

Lastpage

3580

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/WCICA.2008.4593493

Filename

4593493