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

被引：11

作者：

Fontaine, Jaron ^{[1
]}

Van Herbruggen, Ben ^{[1
]}

Shahid, Adnan ^{[1
]}

Kram, Sebastian ^{[2
,3
]}

Stahlke, Maximilian ^{[2
]}

De Poorter, Eli ^{[1
]}

机构：

[1] Univ Ghent, Dept Informat Technol, Imec, B-9052 Ghent, Belgium

[2] Fraunhofer Inst Integrated Circuits IIS, Div Positioning & Networks, D-91058 Nurnberg, Germany

[3] Friedrich Alexander Univ Erlangen Nurnberg FAU, Inst Informat Technol, D-91054 Erlangen, Germany

来源：

IEEE COMMUNICATIONS LETTERS | 2023年 / 27卷 / 05期

关键词：

Fingerprint recognition; Convolutional neural networks; IP networks; Data collection; Location awareness; Information filters; Predictive models; UWB; fingerprinting; neural networks;

D O I：

10.1109/LCOMM.2023.3254146

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

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.

引用

页码：1322 / 1326

页数：5

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