Application of Fuzzy Inferential Combined Kalman Filter in the Docking Guidance System

Author

Li, Guo ; Yang, Guoqing ; Zang, Jinmei

Author_Institution

Coll. of Inf. Sci. & Technol., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China

Volume

1

fYear

2009

fDate

24-26 April 2009

Firstpage

983

Lastpage

986

Abstract

In order to improve the reliability of the Docking Guidance System, an algorithm of the fuzzy combined Kalman filter to fuse information from the vision sensor and the laser sensor separately is proposed in this paper. By monitoring the fluctuation of the measured values, adjusting the state vector covariance of each local filter, using the fuzzy inference system (FIS) and modifying the weight of each fusion data of the main filter, the proposed approach can reduce the disturbance of the fluctuation data prominently. The experimental results show that this algorithm is robust for fluctuation of the measured values and can improve the reliability of the system.

Keywords

Kalman filters; aerospace computing; fuzzy reasoning; sensor fusion; Docking Guidance System; FIS; fuzzy inference system; fuzzy inferential combined Kalman filter; information fusion; laser sensor; state vector covariance; vision sensor; Filters; Fluctuations; Fuses; Fuzzy systems; Inference algorithms; Laser fusion; Monitoring; Robustness; Sensor fusion; Sensor systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on

Conference_Location

Sanya, Hainan

Print_ISBN

978-0-7695-3605-7

Type

conf

DOI

10.1109/CSO.2009.198

Filename

5193858