TY - GEN
T1 - Federated Kalman consensus filter in distributed track fusion
AU - Li, Jiahong
AU - Chen, Jie
AU - Chen, Chen
AU - Deng, Fang
PY - 2013
Y1 - 2013
N2 - Multi-sensor tracking fusion plays a fundamental role in networked information system, especially in the field of fire control systems. According to the diversity, networked and flexible recombined characteristics of the modern information system, a bottom-up architecture of networked information system and the method of track fusion are investigated. Distributed track fusion problem under limited communication is discussed, and federated Kalman consensus filtering(FKCF) algorithm is proposed. Compared to conventional federated filter, FKCF algorithm considers the mobile sensor model, applies Kalman consensus filter to design the sub-filter and designs information-driven method to improve information allocation. The algorithm not only achieves auto recombination and improves survivability, but increases fused tracking accuracy of mobile sensor network with limited communication capability. The experimental results show that FKCF algorithm is better than conventional federated filtering algorithm in track fusion with limited communication.
AB - Multi-sensor tracking fusion plays a fundamental role in networked information system, especially in the field of fire control systems. According to the diversity, networked and flexible recombined characteristics of the modern information system, a bottom-up architecture of networked information system and the method of track fusion are investigated. Distributed track fusion problem under limited communication is discussed, and federated Kalman consensus filtering(FKCF) algorithm is proposed. Compared to conventional federated filter, FKCF algorithm considers the mobile sensor model, applies Kalman consensus filter to design the sub-filter and designs information-driven method to improve information allocation. The algorithm not only achieves auto recombination and improves survivability, but increases fused tracking accuracy of mobile sensor network with limited communication capability. The experimental results show that FKCF algorithm is better than conventional federated filtering algorithm in track fusion with limited communication.
UR - http://www.scopus.com/inward/record.url?scp=84893957990&partnerID=8YFLogxK
U2 - 10.1109/CYBER.2013.6705480
DO - 10.1109/CYBER.2013.6705480
M3 - Conference contribution
AN - SCOPUS:84893957990
SN - 9781479906109
T3 - 2013 IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, IEEE-CYBER 2013
SP - 405
EP - 410
BT - 2013 IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, IEEE-CYBER 2013
T2 - 3rd Annual IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems, IEEE-CYBER 2013
Y2 - 26 May 2013 through 29 May 2013
ER -