测绘学报 ›› 2022, Vol. 51 ›› Issue (6): 862-872.doi: 10.11947/j.AGCS.2022.20220098

• 院士论坛 • 上一篇    下一篇

新型SAR对地环境观测

郭华东1,2,3, 吴文瑾1,2, 张珂1,2,3, 李新武1,2   

  1. 1. 可持续发展大数据国际研究中心, 北京 100094;
    2. 数字地球重点实验室, 中国科学院空天信息创新研究院, 北京 100094;
    3. 中国科学院大学, 北京 100049
  • 收稿日期:2022-02-16 修回日期:2022-04-15 发布日期:2022-07-02
  • 通讯作者: 吴文瑾 E-mail:wuwj@aircas.ac.cn
  • 作者简介:郭华东(1950-),研究员,中国科学院院士、俄罗斯科学院外籍院士、芬兰科学与人文院外籍院士、发展中国家科学院院士,长期从事空间地球信息科学及雷达对地观测研究。E-mail:hdguo@aircas.ac.cn
  • 基金资助:
    中国科学院前沿科学重点研究项目(QYZDY-SSW-DQC026)

New generation SAR for Earth environment observation

GUO Huadong1,2,3, WU Wenjin1,2, ZHANG Ke1,2,3, LI Xinwu1,2   

  1. 1. International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China;
    2. Key Laboratory of Digital Earth Science, Aerospace Information Institute, Chinese Academy of Sciences, Beijing 100094, China;
    3. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2022-02-16 Revised:2022-04-15 Published:2022-07-02
  • Supported by:
    Key Research Program of Frontier Sciences,CAS (No. QYZDY-SSW-DQC026)

摘要: 合成孔径雷达(SAR)系统在对地观测中具有全天时全天候的独特优势。近十几年来,多模式、多角度、多维度、大幅宽、高分辨率、多基协同等SAR技术的问世,代表着新型SAR观测时代的到来。为对这一SAR发展阶段的特点和能力进行分析,本文首先介绍了新型SAR系统观测能力的发展,包括如何获取大范围、多时相、多层次SAR综合对地观测数据及实现月基SAR等观测技术;然后,总结了杂交介质建模、时频分解、深度学习、压缩感知等新型信息提取方法在SAR领域发挥的作用;最后,介绍了新型SAR在城市管理、植被调查、极地与海洋测绘以及灾害监测等领域的研究进展,旨在推动SAR观测技术在测绘领域更广泛而深入的应用。

关键词: 合成孔径雷达, 对地观测, 测绘

Abstract: Synthetic aperture radar (SAR) systems have the unique advantage of all-time and all-weather observation. In the past decade or so, with the continuous announcement of multi-mode, multi-angle, multi-dimension, wide-swath, high-resolution, and multi-static SAR observation technologies, SAR observation has been in the "new generation" stage. This paper first introduces the development of the observation capability of the new generation SAR, including how to realize the wide-swath, multi-temporal, and multi-level observation as well as moon-base observation; Then, the development and application of new information extraction methods such as the non-stationary statistical modeling, time-frequency decomposition, deep learning, and compressed sensing for new generation SAR images are summarized; Finally, recent application progress in urban management, vegetation mapping, polar region and ocean survey, and disaster monitoring are listed to promote wider and deeper applications of the new generation SAR.

Key words: SAR, earth observation, surveying and mapping

中图分类号: