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Multisensor data association is very important in multisensor information fusion, which will decide whether the data from different sensors is representative for the same target. Tradition data association uses the joint probabilistic data association (JPDA) algorithm as the priority means, which depends on the state measurement and has long computation time. So, in this paper, a new algorithm based...
Sensor networks have major applications in environmental monitoring, relief operations, surveillance, health-care and defense. Future sensor networks would comprise of sensing devices with energy harvesting capabilities from renewable energy sources such as solar power. Multiple sensor nodes deployed in the region of interest would collaborate to achieve a global objective, such as detection of application...
Spectrum sensing is the necessary function to achieve spectrum sharing. Distributed and collaborative spectrum sensing can improve the sensing credibility greatly, however when there are too many sensing nodes in the cognitive radio system, for example IEEE802.22 Wireless Regional Area Network system, it will produce large signaling overhead. To reduce the signaling overhead, the selection of sensing...
Building applications on top of sensor data streams is challenging because sensor data is noisy. A model-based view can reduce noise by transforming raw sensor streams into streams of probabilistic state estimates, which smooth out errors and gaps. The authors propose a novel model-based view, the Markovian stream, to represent correlated probabilistic sequences. Applications interested in evaluating...
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