NDLI: Distributed state representation for tracking problems in sensor networks

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Distributed state representation for tracking problems in sensor networks

Content Provider	ACM Digital Library
Author	Zhao, Feng Chu, Maurice Liu, Juan Liu, Jie Reich, Jim
Abstract	This paper investigates the problem of designing decentralized representations to support monitoring and inferences in sensor networks. State-space models of physical phenomena such as those arising from tracking multiple interacting targets, while commonly used in signal processing and control, suffer from the curse of dimensionality as the number of phenomena of interest increases. Furthermore, mapping an inference algorithm onto a distributed sensor network must appropriately allocate scarce sensing and communication resources. We address the state-space explosion problem by developing a distributed state-space model that switches between factored and joint state spaces as appropriate. We develop a collaborative group abstraction as a mechanism to effectively support the information ow within and across subspaces of the state-space model, which can be efficiently supported in a communication-constrained network. The approach has been implemented and demonstrated in a simulation of tracking multiple interacting targets.
Starting Page	234
Ending Page	242
Page Count	9
File Format	PDF
ISBN	1581138466
DOI	10.1145/984622.984657
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2004-04-26
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Group collaboration Multi-target tracking Target localization Sensor network Ad hoc network Information
Content Type	Text
Resource Type	Article

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