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- W2766025411 abstract "Mobile radiation sensor networks integrated with global positioning system coordinates provide an attractive option for the task of dynamically monitoring a region's background radiation and detecting the illicit movement of radioactive materials. Both statistical and probabilistic approaches have been developed for stationary sensor networks to estimate source parameters. In this paper, a pre-filter framework for mobile sensor networks is presented that estimates multiple sources' positions and intensity without prior knowledge about the sources. The pre-filter framework contains a segmentation algorithm, a clustering algorithm and a maximum likelihood estimation algorithm. With adequate number of measurements, the pre-filter framework estimates source parameters in high accuracy. This offers an efficient alternative to traditional approaches where the multi-source problems are difficult to solve." @default.
- W2766025411 created "2017-11-10" @default.
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- W2766025411 date "2016-10-01" @default.
- W2766025411 modified "2023-09-22" @default.
- W2766025411 title "Urban source detection with mobile sensor networks enhanced with machine learning algorithms" @default.
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- W2766025411 doi "https://doi.org/10.1109/nssmic.2016.8069699" @default.
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