Consensus based distributed unscented information filtering for air mobile sensor networks

Authors:
Lin Wang;Nan Wang;Huayong Zhu
Affiliations:
College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha, China;College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha, China;College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha, China
Venue:
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 2
Year:
2010

Citing 4
Cited 0

A scheme for robust distributed sensor fusion based on average consensus

IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Distributed Mobility Management for Target Tracking in Mobile Sensor Networks

IEEE Transactions on Mobile Computing
Distributed information filtering using consensus filters

ACC'09 Proceedings of the 2009 conference on American Control Conference
Decentralized sigma-point information filters for target tracking in collaborative sensor networks

IEEE Transactions on Signal Processing - Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

To the problem of distributed estimation for Mobile Sensor Networks, a new algorithm, named Consensus based Distributed Unscented Information Filter(C_DUIF), was presented, which was based on Unscented Information Filter, Consensus algorithm, as well as a distributed fusion architecture. The proposed algorithm took important properties for estimating accuracy (Unscented Transform), fusion ability (information), robustness (distributed fusion architecture) and distributed consensus. An application of target tracking using an Air Mobile Sensor Networks with dynamically switched network topologies was employed to illustrate the performance of the proposed algorithm. Simulation results showed that the proposed method can significantly improve the accuracy of target position estimation of each sensor node in a distributed fashion, when the distributed consensus between each node was assured.