DocumentCode :
3342567
Title :
Multisensor data synthesis using federated of unscented Kalman filtering
Author :
Ali, Jamshaid ; Jiancheng, Fang
Author_Institution :
Sch. of Instrum. Sci. & Optoelectron. Eng., Beijing Univ. of Aeronaut. & Astronaut.
fYear :
2005
fDate :
14-17 Dec. 2005
Firstpage :
524
Lastpage :
529
Abstract :
In this paper, a decentralized unscented Kalman filter (UKF) in federated configuration is developed for multisensor navigation data fusion. The UKF is a nonlinear, distribution approximation method that uses a finite number of points to propagate the state´s probability distribution through the system´s nonlinear dynamics. In multisensor data fusion application, the configuration features of the federated unscented Kalman filter (FUKF) are investigated. To elaborate the concept of this filter structure, a case study of the strapdown inertial navigation system (SINS) integrated with astronavigation system (ANS) and global positioning system (GPS) is presented. Simulation results demonstrate the validity of the proposed filter configuration
Keywords :
Global Positioning System; Kalman filters; approximation theory; inertial navigation; nonlinear dynamical systems; sensor fusion; statistical distributions; GPS; astronavigation system; distribution approximation method; federated configuration; federated unscented Kalman filter; global positioning system; multisensor data fusion; multisensor data synthesis; navigation data fusion; nonlinear dynamics; probability distribution; strapdown inertial navigation system; Extraterrestrial measurements; Filtering; Kalman filters; Navigation; Remote monitoring; Robot sensing systems; Sensor fusion; Sensor phenomena and characterization; State estimation; Target recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Technology, 2005. ICIT 2005. IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7803-9484-4
Type :
conf
DOI :
10.1109/ICIT.2005.1600694
Filename :
1600694
Link To Document :
بازگشت