A Review of Key Technologies for Fine-Scale InSAR Monitoring of Geological Hazards Along High-Speed Railways
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摘要:
随着我国高速铁路规模持续扩张并向地质环境复杂的中西部地区推进，地表沉降、滑坡、冻土等灾害对铁路结构与运行安全构成严重威胁. 本文系统综述了合成孔径雷达干涉测量（interferometric synthetic aperture radar, InSAR）技术在高铁沿线地质灾害精细监测中的关键技术及研究进展. 首先，梳理国内外主流的“星-空-地”SAR系统，指出星载、机载及地基SAR在“广域普查-重点精查-局部实时”多层级地质灾害监测体系中的优势互补作用. 其次，重点分析保障高铁安全的InSAR地表形变精细监测关键技术，包括：布设人工角反射器（corner reflectors, CR）以解决弱相干区监测难题；构建永久散射体（permanent scatterer, PS）-分布式散射体（distributed scatterer, DS）-CR多级相干目标网络，实现长大铁路沿线地表形变的高精度提取；利用多源数据融合恢复多维度形变场；以及“星-空-地”协同的高时空分辨率形变观测，以弥补单一SAR轨道观测的局限. 最后，探讨当前在复杂环境大气校正及灾害预警等方面面临的挑战，并展望人工智能赋能与多源一体化感知的发展趋势. 本文旨在为高速铁路主动安全监测与风险防控提供关键理论与技术参考.
Abstract:With the continuous expansion of China’s high-speed railway network and its advancement to the central and western regions with complex geological environments, geological hazards such as land subsidence, landslides, and permafrost pose severe threats to the structural and operational safety of railways. The key technologies and research progress of interferometric synthetic aperture radar (InSAR) in the fine-scale monitoring of geological hazards along high-speed railways were systematically reviewed. Firstly, the mainstream Chinese and international “space-air-ground” SAR systems were sorted out, and the complementary advantages of spaceborne, airborne, and ground-based SAR in the multi-level geological hazard monitoring system of “wide-area general survey, detailed survey of key areas, and local real-time monitoring” were pointed out. Secondly, the key technologies for fine-scale InSAR deformation monitoring to ensure high-speed railway safety were emphatically analyzed, including: deploying artificial corner reflectors (CR) to solve the monitoring difficulties in low-coherence areas; constructing a multi-level coherent target network of permanent scatterer (PS)-distributed scatterer (DS)-CR to achieve high-precision extraction of surface deformation along long-distance railways; utilizing multi-source data fusion to recover multi-dimensional deformation fields, and conducting high spatial-temporal resolution deformation observation through “space-air-ground” collaboration to compensate for the limitations of single SAR orbit observation. Finally, the current challenges faced in aspects such as atmospheric correction under complex environments and disaster early warning were discussed, and the development trend of artificial intelligence empowerment and multi-source integrated perception was prospected, so as to provide key theoretical and technical references for the active safety monitoring and risk prevention and control of high-speed railways.
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Key words:
- time-series InSAR /
- high-speed railway /
- geological hazard /
- deformation monitoring /
- SAR system
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图 3 近20年时序InSAR技术发展图
Figure 3. Development of time-series InSAR technology over past 20 years
图 4 面向高铁沿线形变监测的角反射器设计与布设
Figure 4. Design and layout of corner reflectors for deformation monitoring along high-speed railways
图 6 基于PS-DS-CR构网的高铁沿线形变监测
Figure 6. Deformation monitoring along high-speed railways based on PS-DS-CR network
图 9 “星-空-地”InSAR协同观测模式与多平台InSAR数据融合方法
Figure 9. “Space-air-ground” InSAR collaborative observation mode and multi-platform InSAR data fusion method
表 1 现役主要SAR卫星系统参数
Table 1. Parameters of active main SAR satellite systems
卫星名称 发射年份 波段 轨道重访/d 测绘幅宽/km 距离向带宽/MHz 入射角范围/（°） TerraSAR-X 2007 X 11 10～100 150 （最大 300） 15～60 RADARSAT-2 2007 C 24 20～500 100 （最大） 20～50 TanDEM-X 2010 X 11 10～100 150 （最大 300） 15～60 Sentinel-1 （A/C/D） 2014/2024/2025 C 6 （星座） 80～400 100 （最大） 20～46 ALOS-2 2014 L 14 25～490 14～84 8～70 GF-3 （01/02/03） 2016/2021/2022 C 29 10～650 240 （最大） 10～60 ICEYE 2018 X 小时级 5～30 300～600 15～45 SAOCOM-1（A/B） 2018/2020 L 16 40～350 50 （最大） 17～50 RCM 2019 C 4 （星座） 20～500 100 （最大） 14～50 CSG （二代CSK） 2019/2022/2024 X 16 10～200 1200 （最大）20～60 Capella 2020 X 小时级 5～10 500～700 15～45 LT-1 （A/B） 2022 L 4/8 50～400 80 10～60 LT-4 2023 L 1 400～ 1000 +ALOS-4 2024 L 14 200～700 84 （最大） 8～70 NISAR 2025 L/S 12 >240 80（L）/40（S） 34～48 BIOMASS 2025 P 3 45～150 6 23～35 
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表 2 常见InSAR多维形变监测方法对比
Table 2. Comparison of common InSAR multi-dimensional deformation monitoring methods
方法类型 主要数据源 计算形变维度 主要优点 主要局限 单轨 InSAR 单一轨道 SAR（C/L/X 波段） LOS 一维 数据量少、数据处理时间短 仅 LOS 分量，难反映真实运动方向 升降轨 InSAR 升轨 + 降轨 SAR 垂直 + 东西向（准 3D） 无需外业数据、适合廊道连续监测 南北向不敏感 多入射角/多平台 InSAR 不同平台/波段/模式 SAR 垂直 + 水平（增强可观测性） 相干性互补、适应大范围复杂地表 跨平台基准统一复杂、处理流程繁琐 InSAR + GNSS InSAR + GNSS 连续站 三维位移/速度场 三维解算物理意义明确、基准稳定 GNSS 点稀疏、外业成本高 InSAR + 水准 InSAR + 精密水准 水平 + 垂直位移（高精度） 垂直精度高、工程认可度高 水平分量可靠性低 单轨 InSAR + MAI 单一轨道 SAR（C/L/X 波段） LOS + 沿轨向（AT） 可补南北向分量、增强准 3D 监测能力 对相干性敏感 单轨 InSAR + POT 单一轨道SAR（C/L/X 波段） 平面位移（低精度） 适用于大位移和低相干区 精度低 单轨 InSAR + MAI + POT 单一轨道 SAR（C/L/X 波段） 准三维（LOS+AT+ 平面） 多尺度互补、缓变和突变兼顾 流程复杂、误差传播难控制 多源 InSAR + MAI 不同平台/波段 SAR 三维形变场 维度完整、工程解释性强 数据量大，计算效率低；对相干性敏感 多源 InSAR + POT 不同平台/波段 SAR 三维形变场 维度完整、适应于大梯度和低相干区形变 精度低 多源 InSAR + MAI + POT 不同平台/波段 SAR 三维形变场 维度完整、兼顾形变精度和场景复杂性 涉及3种技术，数据处理效率低
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表 3 高速铁路沿线地质灾害InSAR监测关键技术不同场景适用性、作用、优势及解决的工程痛点对比
Table 3. Comparison of applicability, functions, advantages, and solved engineering pain points of key technologies for InSAR monitoring of geological hazards along high-speed railways in different scenarios
场景 项目 人工角反射器（CR） 多级目标构网 多维形变解算 “星-空-地”协同监测 平原沉降区 适用性 强 强 较强 强 作用 提供稳定基准，抑制误差累积，适配线性廊道，可与水准/GNSS 交叉验证 兼顾长大线路覆盖与精度，分层解算提升效率，抑制各类误差累积 获取垂直向沉降和水平向微小位移，助力形变机理解译，弥补 LOS 向监测局限 星载普查 + 机载详查 + 地面精查，实现平原沉降全域高精度监测 山区滑坡区 适用性 强 强 强 强 作用 弥补滑坡区自然相干点不足，捕捉关键部位形变，提升监测可靠性 适配滑坡体散射体不均特点，提升监测点密度，保障形变场连续性 解算滑坡体三维形变，精准判断滑坡滑动方向、速率及稳定性 突破山区地形限制，多平台互补，精准捕捉滑坡边界与动态演化 桥隧重点段 适用性 强 较强 强 强 作用 相位中心稳定，实现构筑物毫米级精准监测 分级构网聚焦关键断面，筛选高质量目标点，提升病害定位精度 解算桥隧三维形变，精准识别结构病害，支撑安全评估 宏观把控 + 微观精细监测，适配桥隧结构精细化运维需求 植被/农田弱相干区 适用性 强 强 一般 强 作用 提供强散射源，解决时空去相干问题，保障监测连续性 联合 CR/DS 弥补相干点稀疏缺陷，实现弱相干区连续监测 实现有限三维形变解算，降低噪声干扰 机载/地面 SAR 弥补星载穿透弱短板，减少弱相干区监测盲区 临灾预警 适用性 较强 较强 强 强 作用 提供高精度先验点位，辅助捕捉临灾微小形变，支撑预警核验 快速筛选高稳定性目标点，获取异常形变，提升预警效率 捕捉三维形变突变特征，研判破坏前兆，弥补 LOS 向误判风险 实现实时监测，突破星载重访局限，形成预警闭环 技术核心优势与解决的工程痛点 提供稳定强散射体，突破地表覆被限制，解决自然相干点稀疏及缺少绝对形变基准等问题 兼顾监测精度与覆盖率，解决大尺度/长距离监测的误差累积，连接孤立形变区 突破单 LOS 盲区，还原真实运动矢量，解决复杂坡体滑移、断层错动等具有显著水平运动特征的形变低估与误判 实现宏观普查、局部详查与微观精查的跨模态融合，弥补星载 InSAR 重访周期长、极高植被穿透弱等短板
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