Paper Info
Title
Efficient Control Of Information Flow For Distributed Multisensor Fusion Using Markov Decision Processes
Abstract
Network-centric multisensor-multitarget tracking has numerous advantages over single-sensor or single-platform tracking. In this paper, we present a solution to one of the main problems of network-centric tracking, namely, decentralized information sharing among the platforms participating in the distributed data fusion. This paper presents a decision mechanism that provides each platform with the required data for the distributed data fusion process while reducing redundancy in the information flow in the overall system. We consider a distributed data fusion system consisting of platforms that are decentralized, heterogenous, and potentially unreliable. The proposed approach, which is based on Markov decision processes and decentralized lookup substrate, will control the information exchange process based, among the other parameters, on tracking performance metrics of individual platforms, thereby enhancing the whole distributed system's reliability as well as that of each participating platform. Simulation examples demonstrate the operation and the performance results of the system.
Year
DOI
Venue
2006
10.1109/ICIF.2006.301722
2006 9th International Conference on Information Fusion, Vols 1-4
Keywords
Field
DocType
distributed data fusion, communication management, control of information flow, Markov decision process, multisensor-multitarget tracking
Information flow (information theory),Markov process,Computer science,Information exchange,Markov decision process,Sensor fusion,Redundancy (engineering),Wireless sensor network,Information sharing,Distributed computing
Conference
Citations 
PageRank 
References 
2
0.41
3
Authors
4
Name
Order
Citations
PageRank
Dmitry Akselrod1112.41
Abhijit Sinha2808.91
Claudia V. Goldman372664.56
Thia Kirubarajan421530.81