Multisensor data fusion schemes for wireless sensor networks Conference Paper

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Overview

abstract

• Data fusion systems is an active research field with applications in several fields such as manufacturing, surveillance, air traffic control, robotics and remote sensing. The wide interest in wireless sensor networks has fueled the interest in data fusion as a medium to compress and interpret the collected data from the spatially distributed sensors. The present paper gives a general overview on the current state of data fusion schemes for wireless sensor networks. Specifically this paper presents a review on some of the commonly used techniques such as Kalman filtering, beamforming, transferable belief model, filter-based techniques and linear mean square estimator. ©2006 IEEE.

authors

• Aguilar Ponce Ruth Mariela
• Baker A.
• Bayoumi M.
• Kumar A.
• McNeely J.

publication date

• 2007-01-01

published in

• Proceedings of the International Conference on Application-Specific Systems, Architectures and Processors  Proceedings

Research

keywords

• Air traffic control; Automation; Control systems; Control theory; Data fusion; Fusion reactions; Hybrid sensors; Industrial research; Information fusion; Nuclear physics; Remote sensing; Sensor networks; Sensors; Signal processing; Space optics; Wireless networks; Wireless sensor networks; Air Traffic; Application-specific systems; Current state; Data-fusion systems; Filter-based; International conferences; Kalman filtering; Mean square estimator; Multi-sensor data fusion; Spatially distributed sensors; Transferable belief model; Sensor data fusion

Identity

Digital Object Identifier (DOI)

• 10.1109/ASAP.2007.4429978

Additional Document Info

start page

• 136

end page

• 141