Title :
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
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;
Conference_Titel :
Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-0-7695-3605-7
DOI :
10.1109/CSO.2009.198
