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  1. Home
  2. Ann-based Lidar Positioning System For B5g.
  1. Home
  2. Ann-based Lidar Positioning System For B5g.

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ANN-Based LiDAR Positioning System for B5G.

Egidio Raimundo Neto1, Matheus Ferreira Silva1, Tomás P V Andrade1

  • 1Laboratory WOCA, National Institute of Telecommunications (Inatel), 510 João de Camargo Av., Santa Rita do Sapucaí 37540-000, MG, Brazil.

Micromachines
|May 25, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces an advanced indoor positioning system using 2D light detection and ranging (LiDAR) and artificial neural networks (ANNs). The system achieves high accuracy for beyond 5G mobile networks, improving pedestrian location mapping.

Keywords:
2D-LiDAR6GB5Gartificial neural networkpositioningsensing

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Area of Science:

  • Robotics and Automation
  • Wireless Communication Systems
  • Artificial Intelligence

Background:

  • Beyond fifth-generation (B5G) mobile networks require sophisticated indoor sensing and positioning.
  • Traditional radiofrequency-based methods face limitations in accuracy and electromagnetic interference.
  • Accurate indoor positioning is crucial for optimizing network functionalities like antenna array control.

Purpose of the Study:

  • To develop an efficient and precise indoor positioning system for B5G networks.
  • To leverage 2D light detection and ranging (LiDAR) technology enhanced by artificial neural networks (ANNs).
  • To overcome the challenges of sensing and positioning in complex indoor environments.

Main Methods:

  • Implementation of a 2D-LiDAR system integrated with an artificial neural network (ANN).
  • Utilizing 2D-LiDAR sensors for data acquisition and digital filters for signal enhancement.
  • Employing a camera and image-processing for automated ANN training sample labeling.
  • Main Results:

    • The system demonstrated high performance in mapping pedestrian locations.
    • Achieved a precision of up to 98.787%, accuracy of 95.25%, recall of 98.537%, and an F1 score of 98.571%.
    • ANN robustness against electromagnetic interference confirmed superior performance over RF methods.

    Conclusions:

    • The proposed 2D-LiDAR and ANN system offers a reliable and accurate solution for indoor positioning.
    • It effectively addresses the demanding requirements of B5G mobile networks.
    • The system shows significant potential for enhancing indoor sensing and positioning applications.