Terahertz Channel Propagation Characteristics and Their Roles in Environment Sensing

Wanzhu Chang; Jiacheng Liu; Yuheng Song; Wenbo Liu; Peian Li; Xiaopeng Wang; Houjun Sun; Jianjun Ma

doi:10.1109/IRMMW-THz61557.2025.11319615

Terahertz Channel Propagation Characteristics and Their Roles in Environment Sensing

Wanzhu Chang
, Jiacheng Liu
, Yuheng Song
, Wenbo Liu
, Peian Li
, Xiaopeng Wang
, Houjun Sun
, Jianjun Ma^*

^*此作品的通讯作者

Beijing Institute of Technology
Tangshan Research Institute
Radar Operation Control Department
China Meteorological Administration

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

This paper investigates terahertz (THz) channel propagation characteristics and explores their potential for environment sensing. Employing controlled experimental setups utilizing THz time-domain spectroscopy (THz-TDS) and continuous wave (CW) systems, we examine THz sensitivity to atmospheric phenomena and surface textures. A convolutional neural network (CNN) model trained on measured attenuation data demonstrates efficiency in rainfall intensity estimation, achieving a mean absolute percentage error (MAPE) of 7.47%. Furthermore, a Long Short-Term Memory (LSTM) neural network robustly classifies surface roughness under dynamic, high-speed conditions, maintaining classification accuracies above 90% even at simulated urban vehicle speeds.

源语言	英语
主期刊名	50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025
出版商	IEEE Computer Society
ISBN（电子版）	9798350378832
DOI	https://doi.org/10.1109/IRMMW-THz61557.2025.11319615
出版状态	已出版 - 2025
已对外发布	是
活动	50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025 - Espoo, 芬兰期限: 17 8月 2025 → 22 8月 2025

丛书

姓名	International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz
ISSN（印刷版）	2162-2027
ISSN（电子版）	2162-2035

会议

会议	50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025
国家/地区	芬兰
市	Espoo
时期	17/08/25 → 22/08/25

访问文件

10.1109/IRMMW-THz61557.2025.11319615

其它文件与链接

链接到 Scopus 的出版物

引用此

Chang, W., Liu, J., Song, Y., Liu, W., Li, P., Wang, X., Sun, H., & Ma, J. (2025). Terahertz Channel Propagation Characteristics and Their Roles in Environment Sensing. 在 50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025 (International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz). IEEE Computer Society. https://doi.org/10.1109/IRMMW-THz61557.2025.11319615

@inproceedings{9adb0fd4a49d4feca49fdb4cd9fbe7ab,

title = "Terahertz Channel Propagation Characteristics and Their Roles in Environment Sensing",

abstract = "This paper investigates terahertz (THz) channel propagation characteristics and explores their potential for environment sensing. Employing controlled experimental setups utilizing THz time-domain spectroscopy (THz-TDS) and continuous wave (CW) systems, we examine THz sensitivity to atmospheric phenomena and surface textures. A convolutional neural network (CNN) model trained on measured attenuation data demonstrates efficiency in rainfall intensity estimation, achieving a mean absolute percentage error (MAPE) of 7.47\%. Furthermore, a Long Short-Term Memory (LSTM) neural network robustly classifies surface roughness under dynamic, high-speed conditions, maintaining classification accuracies above 90\% even at simulated urban vehicle speeds.",

author = "Wanzhu Chang and Jiacheng Liu and Yuheng Song and Wenbo Liu and Peian Li and Xiaopeng Wang and Houjun Sun and Jianjun Ma",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025 ; Conference date: 17-08-2025 Through 22-08-2025",

year = "2025",

doi = "10.1109/IRMMW-THz61557.2025.11319615",

language = "English",

series = "International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz",

publisher = "IEEE Computer Society",

booktitle = "50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025",

address = "United States",

}

Chang, W, Liu, J, Song, Y, Liu, W, Li, P, Wang, X, Sun, H & Ma, J 2025, Terahertz Channel Propagation Characteristics and Their Roles in Environment Sensing. 在 50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025. International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz, IEEE Computer Society, 50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025, Espoo, 芬兰, 17/08/25. https://doi.org/10.1109/IRMMW-THz61557.2025.11319615

Terahertz Channel Propagation Characteristics and Their Roles in Environment Sensing. / Chang, Wanzhu; Liu, Jiacheng; Song, Yuheng 等.
50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025. IEEE Computer Society, 2025. (International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Terahertz Channel Propagation Characteristics and Their Roles in Environment Sensing

AU - Chang, Wanzhu

AU - Liu, Jiacheng

AU - Song, Yuheng

AU - Liu, Wenbo

AU - Li, Peian

AU - Wang, Xiaopeng

AU - Sun, Houjun

AU - Ma, Jianjun

PY - 2025

Y1 - 2025

N2 - This paper investigates terahertz (THz) channel propagation characteristics and explores their potential for environment sensing. Employing controlled experimental setups utilizing THz time-domain spectroscopy (THz-TDS) and continuous wave (CW) systems, we examine THz sensitivity to atmospheric phenomena and surface textures. A convolutional neural network (CNN) model trained on measured attenuation data demonstrates efficiency in rainfall intensity estimation, achieving a mean absolute percentage error (MAPE) of 7.47%. Furthermore, a Long Short-Term Memory (LSTM) neural network robustly classifies surface roughness under dynamic, high-speed conditions, maintaining classification accuracies above 90% even at simulated urban vehicle speeds.

AB - This paper investigates terahertz (THz) channel propagation characteristics and explores their potential for environment sensing. Employing controlled experimental setups utilizing THz time-domain spectroscopy (THz-TDS) and continuous wave (CW) systems, we examine THz sensitivity to atmospheric phenomena and surface textures. A convolutional neural network (CNN) model trained on measured attenuation data demonstrates efficiency in rainfall intensity estimation, achieving a mean absolute percentage error (MAPE) of 7.47%. Furthermore, a Long Short-Term Memory (LSTM) neural network robustly classifies surface roughness under dynamic, high-speed conditions, maintaining classification accuracies above 90% even at simulated urban vehicle speeds.

UR - https://www.scopus.com/pages/publications/105032756047

U2 - 10.1109/IRMMW-THz61557.2025.11319615

DO - 10.1109/IRMMW-THz61557.2025.11319615

M3 - Conference contribution

AN - SCOPUS:105032756047

T3 - International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz

BT - 50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025

PB - IEEE Computer Society

T2 - 50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025

Y2 - 17 August 2025 through 22 August 2025

ER -

Chang W, Liu J, Song Y, Liu W, Li P, Wang X 等. Terahertz Channel Propagation Characteristics and Their Roles in Environment Sensing. 在 50th International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz 2025. IEEE Computer Society. 2025. (International Conference on Infrared, Millimeter, and Terahertz Waves, IRMMW-THz). doi: 10.1109/IRMMW-THz61557.2025.11319615

Terahertz Channel Propagation Characteristics and Their Roles in Environment Sensing

摘要

丛书

会议

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学术指纹

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