Modelling the Four-Dimensional Power Line Sag Dynamics by Point Signature in Time-Series Synthetic-Aperture Radar Images

Sijie Ma; Tao Li; Mahdi Motagh; Yan Liu; Yangmao Wen

doi:10.1049/hve2.70188

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Modelling the Four-Dimensional Power Line Sag Dynamics by Point Signature in Time-Series Synthetic-Aperture Radar Images

更新时间：2026-10-08

- Modelling the Four-Dimensional Power Line Sag Dynamics by Point Signature in Time-Series Synthetic-Aperture Radar Images
- Modelling the Four-Dimensional Power Line Sag Dynamics by Point Signature in Time-Series Synthetic-Aperture Radar Images
- 高电压（英文） 2026年11卷第4期
- 作者机构：
  
  1. GNSS Research Center, Wuhan University,Wuhan,China
  2. School of Geodesy and Geomatics, Wuhan University,Wuhan,China
  3. Hubei Luojia Laboratory,Wuhan,China
  4. ,and
  5. Mahdi Motagh
  6. Section of Remote Sensing and Geoinformatics, GFZ Helmholtz Centre for Geosciences,Potsdam,Germany
  7. Institute of Photogrammetry and Geoinformation, Leibniz University Hannover,Hannover,Germany
  8. Tao Li
  9. State Key Laboratory of Power Grid Environmental Protection, China Electric Power Research Institute,Wuhan,China
- 作者简介：
- 基金信息：
- DOI：10.1049/hve2.70188
  中图分类号：
- 纸质出版：2026
- 稿件说明：
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Sijie Ma, Tao Li, Mahdi Motagh, 等. Modelling the Four-Dimensional Power Line Sag Dynamics by Point Signature in Time-Series Synthetic-Aperture Radar Images[J]. 高电压（英文）, 2026,11(4).

Sijie Ma, Tao Li, Mahdi Motagh, et al. Modelling the Four-Dimensional Power Line Sag Dynamics by Point Signature in Time-Series Synthetic-Aperture Radar Images[J]. High Voltage, 2026, 11(4).
Sijie Ma, Tao Li, Mahdi Motagh, 等. Modelling the Four-Dimensional Power Line Sag Dynamics by Point Signature in Time-Series Synthetic-Aperture Radar Images[J]. 高电压（英文）, 2026,11(4). DOI： 10.1049/hve2.70188.

Sijie Ma, Tao Li, Mahdi Motagh, et al. Modelling the Four-Dimensional Power Line Sag Dynamics by Point Signature in Time-Series Synthetic-Aperture Radar Images[J]. High Voltage, 2026, 11(4). DOI： 10.1049/hve2.70188.

摘要

Abstract

Power lines in synthetic-aperture radar (SAR) images are reflected as point signatures

which fluctuate annually in both the azimuth and range directions. A novel framework is proposed in this paper to evaluate the four-dimensional dynamic status of power line sag using those point signatures in time-series SAR images. An inversion model is proposed to reconstruct the three-dimensional power line sag profile based on the point signature positions and power line suspension points in the SAR coordinates. By combining the elevation function and the power line parabolic function derived in the SAR image

the 3D geometry of power line sag can be reconstructed using the range–Doppler model. A sag–temperature model is proposed to evaluate the 4D dynamic status of power lines in time-series SAR images. The results show that the proposed model has been able to identify one of the power line sag failure events in the study area

which occurred around September 2016

with an approximate 2.54-m line sudden sag downward. This case study shows the potential of spaceborne SAR for real-time power line sag monitoring

particularly under extreme weather conditions.

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