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Updated: Aug 30, 2025

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Indoor Positioning System with UWB Based on a Digital Twin.

Ping Lou1, Qi Zhao1, Xiaomei Zhang1

  • 1School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China.

Sensors (Basel, Switzerland)
|August 26, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a digital twin-enhanced Ultra-wideband (UWB) system for improved indoor positioning. It addresses non-line-of-sight challenges using a cyber-physical feedback loop and neural networks for greater accuracy.

Keywords:
NLOS errordigital twinindoor positioning system (IPS)ultra-wideband (UWB)

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Area of Science:

  • Robotics and Automation
  • Wireless Communication Systems
  • Geographic Information Systems

Background:

  • Ultra-wideband (UWB) technology offers high precision for indoor positioning.
  • Non-line-of-sight (NLOS) conditions caused by indoor obstacles significantly degrade UWB positioning accuracy.
  • Dynamic and complex indoor environments pose persistent challenges for reliable positioning.

Purpose of the Study:

  • To present an advanced indoor positioning system utilizing Ultra-wideband (UWB) technology integrated with a digital twin framework.
  • To enhance positioning accuracy in challenging indoor environments by mitigating Non-Line-of-Sight (NLOS) signal propagation issues.
  • To introduce novel methods for anchor deployment and error correction within the UWB positioning system.

Main Methods:

  • Development of an indoor positioning system combining UWB with a digital twin model.
  • Implementation of a perception-prediction feedback loop within the cyber-physical space.
  • Introduction of a virtual-reality interactive anchor layout optimization strategy.
  • Application of neural network-based algorithms for error mitigation in UWB positioning.

Main Results:

  • The proposed digital twin-based UWB system demonstrates a significant improvement in indoor positioning accuracy.
  • The integration of cyber-physical feedback effectively addresses NLOS propagation challenges.
  • The neural network error mitigation and optimized anchor layout contribute to enhanced system performance.
  • A case study validates the substantial accuracy gains achieved by the system.

Conclusions:

  • The digital twin-enhanced UWB indoor positioning system offers a robust solution for complex environments.
  • The developed methods for anchor layout and error correction are effective in improving positioning precision.
  • This approach provides a significant advancement in achieving reliable and accurate indoor localization.