Ultra Wideband (UWB) Localization Using Active CIR-Based Fingerprinting

IEEE Communications Letters(2023)

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摘要
Indoor positioning systems using Ultra Wideband (UWB) achieve high positioning accuracy (<30 cm). How-ever, traditional localization approaches require many packet exchanges (e.g. two-way ranging) or challenging clock syn-chronization (e.g. time difference of arrival). To remedy this, we propose active fingerprinting using the channel impulse response (CIR) from a single UWB packet received at each UWB anchor. The proposed neural network anchor-subset selection method with Savitzky-Golay filter achieves a low mean absolute error (20.9 - 87.0 cm), in contrast to signal strength based fingerprinting approaches that realize accuracies of 2 - 3 m. Finally, with CIR interpolation the data collection overhead is reduced.
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关键词
Fingerprint recognition,Convolutional neural networks,IP networks,Data collection,Location awareness,Information filters,Predictive models,UWB,fingerprinting,neural networks
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