中国安全科学学报 ›› 2025, Vol. 35 ›› Issue (S2): 216-222.doi: 10.16265/j.cnki.issn1003-3033.2025.S2.0028

• 防灾减灾技术与工程 • 上一篇    下一篇

基于GB-SAR的水电站边坡安全监测精度提升与验证方法

候杉山1,2(), 杨晓琳1,2, 白兴平3, 王康3, 高焕焕3, 张群3   

  1. 1 中国安全生产科学研究院, 北京 100012
    2 中安国泰(北京)科技发展有限公司, 北京 102209
    3 中国电建集团西北勘测设计研究院有限公司, 陕西 西安 710065
  • 收稿日期:2025-08-25 出版日期:2026-02-04
  • 作者简介:

    候杉山 (1995—),男,河北承德人,硕士,工程师,主要从事地基合成孔径雷达技术等方面的工作。E-mail:

    杨晓琳 正高级工程师

  • 基金资助:
    应急管理部重点科技计划项目(2024EMST080802)

Accuracy improvement and validation of GB-SAR-based slope safety monitoring at a hydropower station

HOU Shanshan1,2(), YANG Xiaolin1,2, BAI Xingping3, WANG Kang3, GAO Huanhuan3, ZHANG Qun3   

  1. 1 China Academy of Safety Science and Technology, Beijing 100012, China
    2 Cathay Safety Technology Co., Ltd., Beijing 102209, China
    3 Power China Northwest Engineering Corporation Limited, Xi'an Shaanxi 710065, China
  • Received:2025-08-25 Published:2026-02-04

摘要:

为提升地基合成孔径雷达(GB-SAR)在水电站高陡、高湿复杂边坡环境下的形变监测精度,选取青海省某水电站库区典型边坡为试验区,设计布设了雷达角反射器与全站仪棱镜刚性固定联合标靶,并在稳定对岸架设GB-SAR及全站仪;通过定量精密控制联合标靶位移量(作为位移真值),系统开展GB-SAR精度验证试验;基于高精度基准数据评估结果,重点优化GB-SAR相位信号处理中的滤波算法,并提出一种融合地形梯度加权与相位稳定性指数的自适应空时联合滤波方法。结果表明:经算法优化,GB-SAR在复杂水电站边坡环境下对点目标的形变监测精度稳定提升至0.1 mm级。所提出的定量位移验证方法及有效算法优化策略,能够显著提升GB-SAR在恶劣环境下的监测精度,为水电站边坡安全预警提供精准可靠的技术支撑。

关键词: 地基合成孔径雷达(GB-SAR), 水电站边坡, 形变监测, 角反射器, 滤波算法

Abstract:

To enhance the deformation monitoring accuracy of GB-SAR in the complex slope environments of hydropower stations characterized by high steepness and humidity, a typical slope in the reservoir area of a hydropower station in Qinghai Province was selected as the test site. A rigidly fixed combined target integrating radar corner reflectors and total station prisms was designed and deployed, while both GB-SAR and a total station were set up on the stable opposite bank. The displacement of the combined target, serving as the true value, was quantitatively and precisely controlled to systematically conduct a GB-SAR accuracy validation experiment. Based on the evaluation results from high-precision benchmark data, the filtering algorithm within the GB-SAR phase signal processing chain was optimized, and an adaptive spatiotemporal filtering method incorporating terrain gradient weighting and a phase stability index was proposed. The results indicate that after algorithmic optimization, the deformation monitoring accuracy of GB-SAR for point targets in complex hydropower station slope environments is consistently improved to the submillimeter level (0.1 mm). The proposed quantitative displacement verification method and effective algorithmic optimization strategy significantly enhance the monitoring accuracy of GB-SAR in harsh environments and provide precise and reliable technical support for early warning of slope safety at hydropower stations.

Key words: ground-based synthetic aperture radar (GB-SAR), hydropower station slope, deformation monitoring, corner reflector, filtering algorithm

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