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- W2016647441 abstract "In wireless body area sensor networking (WBASN) applications such as gastrointestinal (GI) tract monitoring using wireless video capsule endoscopy (WCE), the performance of out-of-body wireless link propagating through different body media (i.e. blood, fat, muscle and bone) is still under investigation. Most of the localization algorithms are vulnerable to the variations of path-loss coefficient resulting in unreliable location estimation. In this paper, we propose a novel robust probabilistic Bayesian-based approach using received-signal-strength (RSS) measurements that accounts for Rayleigh fading, variable path-loss exponent and uncertainty in location information received from the neighboring nodes and anchors. The results of this study showed that the localization root mean square error of our Bayesian-based method was 1.6 mm which was very close to the optimum Cramer-Rao lower bound (CRLB) and significantly smaller than that of other existing localization approaches (i.e. classical MDS (64.2mm), dwMDS (32.2mm), MLE (36.3mm) and POCS (2.3mm))." @default.
- W2016647441 created "2016-06-24" @default.
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- W2016647441 date "2014-08-01" @default.
- W2016647441 modified "2023-09-27" @default.
- W2016647441 title "Bayesian-based localization of wireless capsule endoscope using received signal strength" @default.
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- W2016647441 doi "https://doi.org/10.1109/embc.2014.6944993" @default.
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