Applying NLOS Classification and Error Correction Techniques to UWB Systems: Lessons Learned and Recommendations-Reference-Cited by-同舟云学术

Applying NLOS Classification and Error Correction Techniques to UWB Systems: Lessons Learned and Recommendations

Published:2023-05-09 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of Cyber-Physical Systems and Internet of Things Week 2023
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Author:

Stocker Michael¹^ORCID,Gallacher Markus¹^ORCID,Boano Carlo Alberto¹^ORCID,Roemer Kay¹^ORCID

Affiliation:

1. Institute for Technical Informatics, Graz University of Technology, Austria

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3576914.3587522

Reference14 articles.

1. S. Angarano 2021. Robust UWB Range Error Mitigation with Deep Learning at the Edge. Engineering Applications of Artificial Intelligence 102 ( 2021 ). S. Angarano 2021. Robust UWB Range Error Mitigation with Deep Learning at the Edge. Engineering Applications of Artificial Intelligence 102 (2021).

2. V. Barral 2019. NLOS Identification and Mitigation Using Low-Cost UWB Devices. Sensors 19, 16 ( 2019 ). V. Barral 2019. NLOS Identification and Mitigation Using Low-Cost UWB Devices. Sensors 19, 16 (2019).

3. Decision theoretic framework for NLOS identification

4. K. Bregar 2018. Improving Indoor Localization Using Convolutional Neural Networks on Computationally Restricted Devices . IEEE Access 6 ( 2018 ). K. Bregar 2018. Improving Indoor Localization Using Convolutional Neural Networks on Computationally Restricted Devices. IEEE Access 6 (2018).

5. Decawave. 2017. DW1000 User Manual version 2.11. Decawave. 2017. DW1000 User Manual version 2.11.

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