多模式遥感智能信息与目标识别:微波视觉的物理智能

金亚秋

金亚秋. 多模式遥感智能信息与目标识别:微波视觉的物理智能[J]. 雷达学报, 2019, 8(6): 710–716. doi: 10.12000/JR19083
引用本文: 金亚秋. 多模式遥感智能信息与目标识别:微波视觉的物理智能[J]. 雷达学报, 2019, 8(6): 710–716. doi: 10.12000/JR19083
JIN Yaqiu. Multimode remote sensing intelligent information and target recognition: Physical intelligence of microwave vision[J]. Journal of Radars, 2019, 8(6): 710–716. doi: 10.12000/JR19083
Citation: JIN Yaqiu. Multimode remote sensing intelligent information and target recognition: Physical intelligence of microwave vision[J]. Journal of Radars, 2019, 8(6): 710–716. doi: 10.12000/JR19083

多模式遥感智能信息与目标识别:微波视觉的物理智能

DOI: 10.12000/JR19083
基金项目: 国家自然科学基金重大项目“合成孔径雷达微波视觉三维成像理论与应用基础研究”(61991422, 61991420)
详细信息
    作者简介:

    金亚秋(1946–),男,上海人,美国麻省理工学院博士学位,教授,复旦大学电磁波信息科学教育部重点实验室主任,中国科学院院士,研究方向为复杂自然介质的电磁辐射、散射与传输。E-mail: yqjin@fudan.edu.cn

    通讯作者:

    金亚秋 yqjin@fudan.edu.cn

  • 责任主编:仇晓兰 Corresponding Editor: QIU Xiaolan
  • 中图分类号: TN957.52

Multimode Remote Sensing Intelligent Information and Target Recognition: Physical Intelligence of Microwave Vision (in English)

Funds: The Major Program of National Natural Science Foundation of China “Research on SAR Microwave Vision Three-Dimensional Imaging Theory and Application Fundation” (61991422, 61991420)
More Information
  • 摘要: 多模式高分辨率合成孔径雷达(SAR)的发展,对天空地海环境目标信息感知与特征获取提出了新的挑战,空间遥感大数据与人工智能信息技术的交叉是自动目标识别(ATR)一个新的研究方向与重大应用领域。该文提出,在电磁波与目标相互作用的物理背景下进行人工智能信息技术的研究,即“物理智能”,以发展在人眼不能识别的电磁频谱上形成信息感知的“微波视觉”,实现多模式遥感智能信息与目标识别。该文主要内容基于作者2019年8月15日在“雷达学报第五届青年科学家论坛”上的学术报告。

     

  • 图  1  MIT斯迪塔科学中心

    Figure  1.  MIT stata science center

    图  2  大厅中陈列的SCR-615B雷达

    Figure  2.  SCR-615B radar displayed in the hall

    图  3  各国SAR发展概况

    Figure  3.  Overview of SAR development in various countries

    图  4  天空地海目标的多源多模式SAR遥感信息感知研究与应用

    Figure  4.  Research and application of multi-source and multi-mode SAR remote sensing information perception for spatial-ground-sea targets

    图  5  遥感大数据的物理智能到应用

    Figure  5.  Physical intelligence to application of remote sensing big data

    图  6  空间电磁学的人工智能

    Figure  6.  Artificial intelligence of space electromagnetics

    图  7  空间微波遥感研究与应用丛书

    Figure  7.  Spatial microwave remote sensing research and application series

    图  1  MIT Stata Science Center

    图  2  SCR-615B radar displayed in the hall

    图  3  Overview of SAR development in various countries

    图  4  Research and application of multisource and multimode SAR remote sensing information perception for space-ground-sea targets

    图  5  Physical intelligence to application of remotely sensed big data

    图  6  Artificial intelligence of space electromagnetics

    图  7  Spaceborne microwave remote sensing research and application series

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出版历程
  • 收稿日期:  2019-09-17
  • 修回日期:  2019-11-29
  • 网络出版日期:  2019-12-01

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