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<p>The tunnel construction industry faces critical challenges including fragmented communication positioning systems, structural complexity, and deployment inefficiencies‌. This study aims to investigate an integrated, simplified technologies for unified communication and positioning in tunnel environments‌. Specifically, the channel state information from both the time and frequency domains is analyzed, and the differences in signal propagation between tunnel and indoor environments are compared. A novel communication and perception fusion positioning method tailored for tunnel scenarios is proposed. This method combines the moving average algorithm with the random forest classification algorithm, and multiple comparative experiments are conducted at the construction site. The experimental results indicate that the proposed method achieves an accuracy of approximately 92% at a distance resolution of 0.75&#xa0;m. Furthermore, leveraging the one-dimensional characteristics of tunnel construction scenarios and the unidirectional low-speed movement of construction equipment, the proposed positioning method is further optimized via the trend analysis method, resulting in an improved accuracy of 99%. Finally, experiments are conducted using a horizontal transportation locomotive in tunnel construction as the carrier. The results demonstrate that within 106.5&#xa0;m, both test runs were within a 0.5&#xa0;m error range, validating the effectiveness and reliability of the proposed method.</p>

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Communication and perception integrated positioning system in tunnel construction scenarios

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月12日

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  • Yu-song You,
  • Zhong Shen,
  • Liu-jie Jing,
  • Qing-hai Yang

摘要

The tunnel construction industry faces critical challenges including fragmented communication positioning systems, structural complexity, and deployment inefficiencies‌. This study aims to investigate an integrated, simplified technologies for unified communication and positioning in tunnel environments‌. Specifically, the channel state information from both the time and frequency domains is analyzed, and the differences in signal propagation between tunnel and indoor environments are compared. A novel communication and perception fusion positioning method tailored for tunnel scenarios is proposed. This method combines the moving average algorithm with the random forest classification algorithm, and multiple comparative experiments are conducted at the construction site. The experimental results indicate that the proposed method achieves an accuracy of approximately 92% at a distance resolution of 0.75 m. Furthermore, leveraging the one-dimensional characteristics of tunnel construction scenarios and the unidirectional low-speed movement of construction equipment, the proposed positioning method is further optimized via the trend analysis method, resulting in an improved accuracy of 99%. Finally, experiments are conducted using a horizontal transportation locomotive in tunnel construction as the carrier. The results demonstrate that within 106.5 m, both test runs were within a 0.5 m error range, validating the effectiveness and reliability of the proposed method.