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Novel Fine-Tuned Attribute Weighted Naïve Bayes NLoS Classifier for UWB Positioning
In this paper, we propose a novel Fine-Tuned attribute Weighted Na\"ive Bayes (FT-WNB) classifier to identify the Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) for UltraWide Bandwidth (UWB) signals in an Indoor Positioning System (IPS).
Anomaly Detection Based on Generalized Gaussian Distribution approach for Ultra-Wideband (UWB) Indoor Positioning System
The simulation results indicate that the proposed approach can provide a robust NLoS component identification which improves the NLoS signal classification accuracy which results in significant improvement in the UWB positioning system.
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