层析SAR地表参数信息提取研究进展

李震; 张平; 乔海伟; 赵常军; 周建民; 黄磊

doi:10.12000/JR20095

层析SAR地表参数信息提取研究进展

DOI: 10.12000/JR20095

李震^{1, 2},
张平^{1, 2, ,},
乔海伟¹,
赵常军¹,
周建民^{1, 2},
黄磊^{1, 2}

1.
中国科学院空天信息创新研究院北京 100094
2.
三亚中科遥感研究所海南省地球观测重点实验室三亚 572029

基金项目: 海南省重点研发计划(ZDYF2019002)，中国科学院空天信息创新研究院重点部署项目(Y950930Z2F)

详细信息

作者简介:
李　震(1966–)，男，湖北武汉人，研究员、博士生导师。主要从事地物目标散射机制、SAR地表参数反演与冰冻圈环境变化等方面的研究。E-mail: lizhen@aircas.ac.cn

张　平(1979–)，女，河北沧州人，高级工程师。主要从事合成孔径雷达信号处理、超分辨率图像处理、极化定标等方面的研究。E-mail: zhangping@aircas.ac.cn

乔海伟(1997–)，男，甘肃张掖人，博士研究生。主要从事雷达干涉、层析雷达、积雪遥感等方面的研究。E-mail: qhwgis@gmail.com

赵常军(1991–)，男，甘肃陇南人，博士研究生。主要从事InSAR技术及应用研究。E-mail: zhaocj@radi.ac.cn

周建民(1978–)，男，山东聊城人，副研究员。主要从事雷达遥感机理与应用、全球变化遥感等方面的研究。E-mail: zhoujm@aircas.ac.cn

黄　磊(1982–)，男，山东邹城人，副研究员，主要从事微波遥感、极化散射机制方面的研究。E-mail: huanglei@radi.ac.cn

通讯作者:
张平 zhangping@aircas.ac.cn

责任主编：廖明生 Corresponding Editor: LIAO Mingsheng
中图分类号: TN957.52
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- 被引次数: 0
出版历程
- 收稿日期: 2020-07-07
- 修回日期: 2020-09-02
- 网络出版日期: 2021-02-25

Advances in Information Extraction of Surface Parameters Using Tomographic SAR

LI Zhen^{1, 2},
ZHANG Ping^{1, 2
, ,},
QIAO Haiwei¹,
ZHAO Changjun¹,
ZHOU Jianmin^{1, 2},
HUANG Lei^{1, 2}

1.
Aerospace Information Research Institute, Chinese Academy of Science, Beijing 100094, China
2.
Key Laboratory of Earth Observation of Hainan Province, Sanya Institute of Remote Sensing, Sanya 572029, China

Funds: The Key Research and Development Program of Hainan Province (ZDYF2019002), The Key Deployment Program of AIRCAS (Y950930Z2F)

More Information

Corresponding author: ZHANG Ping, zhangping@aircas.ac.cn

摘要

摘要: 传统的合成孔径雷达(SAR)成像是将现实中的三维场景投影到方位-斜距向二维平面的一系列处理过程，损失了三维空间的高度维信息。随着SAR系统及处理技术的发展，层析SAR系统通过沿高度向的多个数据获取构造高度维合成孔径，利用阵列信号处理方法实现目标高分辨率三维成像，对观测场景进行三维重建，获取地面目标的垂直结构信息，对植被监测、雪冰探测、城市建模等应用具有重要应用价值。该文基于层析SAR观测机理，分析了配准、去平地效应、相位补偿、高度维聚焦等三维成像关键环节以及算法研究现状，着重阐述了层析SAR在植被、雪冰、城市信息提取方面的应用，介绍了过去20年中相关的实验结果，讨论了不同平台下植被高度与冠层结构、冰川厚度与内部结构、积雪厚度与分层、城市区三维重建与形变监测等方面的应用潜力与存在的问题，并对其发展趋势进行了展望。
- 层析SAR /
- 多基线SAR /
- 地表参数 /
- 垂直结构 /
- 冰川厚度 /
- 积雪分层
Abstract: Traditional Synthetic Aperture Radar (SAR) imaging is the projection of a real three-dimensional scene onto a two-dimensional domain of azimuth and slant range, which results in the loss of the high-dimensional information. With the advancement of SAR system and its processing technology, tomographic SAR systems obtain multiple data along the height direction to construct the high-dimensional synthetic aperture, and use array signal processing methods to achieve high-resolution three-dimensional images. It can reconstruct the observation scene and extract vertical structure information of the ground target, which is very important for vegetation monitoring, snow and ice detecting, and urban modeling. This paper analyzed the key steps of three-dimensional imaging, such as image registration, flat-earth phase removal, phase compensation, and the three-dimensional focusing, as well as the current research status of each step based on the observation mechanism of tomographic SAR system. This paper particularly focuses on using tomographic SAR on the application of vegetation, glacier, snow, and urban information. The most relevant experimental results in the past two decades were introduced. Further, the application potential and existing problems related to the vegetation height with canopy structure, glacier thickness with internal structure, snow thickness with stratification, and urban three-dimensional reconstruction with deformation monitoring under different platforms are discussed. Finally, the prospects of TomoSAR in the primary applications field are presented.
- Tomographic SAR /
- Multi-baseline SAR /
- Surface parameters /
- Vertical structure /
- Glacier thickness /
- Snow stratification

HTML全文

图 1 层析SAR观测机理

Figure 1. Tomographic SAR observation mechanism

下载: 全尺寸图片幻灯片

图 2 层析SAR处理流程

Figure 2. Tomographic SAR processing flow

下载: 全尺寸图片幻灯片

图 3 差分干涉相位，其时间基线和空间基线是490 d和97.7 m

Figure 3. Differential interferograms with temporal baseline of 490 days and spatial baseline of 97.7 m

下载: 全尺寸图片幻灯片

图 4 人造目标成像结果对比

Figure 4. Manmade targets imaging results comparison

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图 5 TomoSAR反演的森林树高切片^[44]

Figure 5. Forest tree height transects inverted by TomoSAR^[44]

下载: 全尺寸图片幻灯片

图 6 阿尔卑斯山冰川反演实验^[61]

Figure 6. Reversion experiment of Alps Glacier^[61]

下载: 全尺寸图片幻灯片

图 7 地基层析SAR积雪结构观测结果^[11]

Figure 7. Snow structure observation result of ground based tomography SAR^[11]

下载: 全尺寸图片幻灯片

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