Title :
Active and dynamic multi-sensor information fusion method based on Dynamic Bayesian Networks
Author :
Han, Pengxin ; Mu, Rongjun ; Cui, Naigang
Author_Institution :
Dept. of Space Eng., Harbin Inst. of Technol., Harbin, China
Abstract :
In order to improve the dynamic optimization capability and fault-tolerant ability of the information fusion method for multi-sensor system, the theory of dynamic Bayesian networks was used to rebuild the conventional federated Kalman filter in this paper, and a new kind of active and dynamic information fusion and optimization method for multisensor systems under high-dynamic situation was proposed. The simulation results indicated the high dynamic flexibility and fault-tolerant ability of the proposed method.
Keywords :
Kalman filters; belief networks; fault tolerance; optimisation; sensor fusion; active multisensor information fusion method; dynamic Bayesian networks; dynamic multisensor information fusion method; dynamic optimization method; fault-tolerant ability; federated Kalman filter; Aerodynamics; Bayesian methods; Fault tolerance; Intelligent sensors; Mechatronics; Navigation; Optimization methods; Sensor fusion; Space vehicles; Vehicle dynamics; Dynamic Bayesian networks; Dynamic information fusion; Multi-sensor system;
Conference_Titel :
Mechatronics and Automation, 2009. ICMA 2009. International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4244-2692-8
Electronic_ISBN :
978-1-4244-2693-5
DOI :
10.1109/ICMA.2009.5246072
