DESIGNING A FUSION-DRIVEN SENSOR NETWORK TO SELECTIVELY TRACK MOBILE TARGETS
Abstract
Sensor networks that can support time-critical operations pose challenging problems for tracking events of interest. We propose an architecture for a sensor network that autonomously adapts in real-time to data fusion requirements so as not to miss events of interest and provides accurate real-time mobile target tracking. In the proposed architecture, the sensed data is processed in an abstract space called Information Space and the communication between nodes is modeled as an abstract space called Network Design Space. The two abstract spaces are connected through an interaction interface called InfoNet, that seamlessly translates the messages between the two. The proposed architecture is validated experimentally on a laboratory testbed for multiple scenarios.
This material is based upon work supported by, or in part by, the U. S. Army Research Laboratory and the U. S. Army Research Office under the eSensIF MURI Award No. W911NF-07-1-0376. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the sponsor.
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