智能电磁感知的若干进展

李廉林 崔铁军

李廉林, 崔铁军. 智能电磁感知的若干进展[J]. 雷达学报, 2021, 10(2): 183–190. doi: 10.12000/JR21049
引用本文: 李廉林, 崔铁军. 智能电磁感知的若干进展[J]. 雷达学报, 2021, 10(2): 183–190. doi: 10.12000/JR21049
LI Lianlin and CUI Tiejun. Recent progress in intelligent electromagnetic sensing[J]. Journal of Radars, 2021, 10(2): 183–190. doi: 10.12000/JR21049
Citation: LI Lianlin and CUI Tiejun. Recent progress in intelligent electromagnetic sensing[J]. Journal of Radars, 2021, 10(2): 183–190. doi: 10.12000/JR21049

智能电磁感知的若干进展

doi: 10.12000/JR21049
基金项目: 国家重点研发计划变革性关键技术项目(2017YFA0700201/02/03)
详细信息
    作者简介:

    李廉林(1980–),男,山西人,北京大学信息科学技术学院教授、博士生导师。近年来,从事电磁感知体制、算法和工程应用方面的教学科研工作。主持国家自然科学基金等项目课题,以第一/通信作者在Nature Communications, Advanced Science, IEEE等发表论文80余篇,申请/授权国家发明专利20余项,出版中英文学术专著各1部。部分研究成果在电离层探测、石油探测和无线通信等领域得到应用。E-mail: lianlin.li@pku.edu.cn

    崔铁军(1965–),男,中国科学院院士,东南大学首席教授,IEEE Fellow,长期从事电磁超材料和计算电磁学研究。1993年获西安电子科技大学博士学位,1995—2002年先后任职德国洪堡学者、美国UIUC博士后和研究科学家。2001年受聘东南大学长江学者特聘教授;2002年获得国家杰出青年科学基金。2014年创建信息超材料新方向。发表学术论文500余篇,被引用35000余次、H因子93(谷歌学术)。研究成果入选2010年中国科学十大进展、2016年中国光学重要成果;获2011年教育部自然科学一等奖、2014年国家自然科学二等奖、2016年军队科学技术进步一等奖、2018年国家自然科学二等奖。E-mail: tjcui@seu.edu.cn

    通讯作者:

    李廉林 lianlin.li@pku.edu.cn

  • 责任主编:冯一军 Corresponding Editor: FENG Yijun
  • 中图分类号: TN82

Recent Progress in Intelligent Electromagnetic Sensing

Funds: The National Key Research and Development Program of China (2017YFA0700201/02/03)
More Information
  • 摘要: 智能电磁感知是电磁探测与成像的系统化和智能化延伸,是安全检查、生物医学、物联网等领域的基础性、关键性和共性问题。近年来,挖掘利用人工电磁材料和人工智能在电磁波调控与数据信息调控方面的强大能力,将其有机结合,并系统地引入电磁感知领域,发展了低成本、高性能的智能电磁感知体制,为电磁感知的进一步发展提供了关键理论和技术支撑。该文讨论了智能电磁感知的若干最新进展,为读者及时掌握该领域的最新进展提供有益帮助。

     

  • 图  1  首个可编程数字编码超材料的基本概念和部分结果[13]

    (a)1比特相移键控可编程数字编码超材料示意图 (b)1比特相移键控可编程数字编码超材料的单元结构及其相位-频率响应曲线 (c)1比特相移键控可编程数字编码超材料的在波束扫描中的若干应用 (d)1比特相移键控可编程数字编码超材料的基本工作原理

    Figure  1.  Concepts and Results of the first programmable digital coding metamaterials[13]

    (a) The schematic diagram of 1-bit phase-shift programmable digital coding metamaterial (b) The element structure of 1-bit phase-shift programmable digital coding metamaterial and its phase frequency characteristic curves (c) 1-bit phase-shift programmable digital coding metamaterial in beam scanning applications (d) The basic working principle of 1-bit phase-shift programmable digital coding metamaterial

    图  2  信息超材料的发展历史和趋势[19]

    Figure  2.  The history and trend of information metamaterials[19]

    图  3  经典机器学习驱动的智能电磁感知成像原理和部分结果[24]

    (a)主分量机器学习方法驱动的智能电磁感知的工作原理示意图 (b)基于2比特信息超材料的智能电磁感知系统示意图 (c)2比特相移键控信息超材料及单元结构示意图 (d)不同成像人体目标的光学图片 (e)基于主分量机器学习驱动智能电磁感知的成像结果 (f)基于随机降维机器学习驱动智能电磁感知的成像结果

    Figure  3.  The imaging principle and results of intelligent electromagnetic sensing driven by classical machine learning[24]

    (a) The schematic diagram of the principle of intelligent electromagnetic sensing driven by principal component machine learning (b) The schematic diagram of intelligent electromagnetic sensing system based on 2-bit information metamaterial (c) The schematic diagram of 2-bit phase-shift information metamaterial and element structure (d) The optical images of different human targets (e) The imaging results of intelligent electromagnetic sensing driven by principal component machine learning (f) The imaging result of intelligent electromagnetic sensing driven by machine learning based on random dimension reduction

    图  4  深度学习驱动的智能电磁感知成像原理和部分结果[25]

    (a)智能电磁感知的工作原理示意图 (b)基于1比特信息超材料的智能电磁感知系统示意图 (c)不同成像人体目标的光学图片及其成像结果 (d)基于智能感知系统的感兴趣人体局部姿势的波束聚焦结果 (e)基于智能感知系统的10个英文字母的手语识别结果 (f)基于智能感知系统的2个人体的呼吸特征识别结果

    Figure  4.  The imaging principle and results of intelligent electromagnetic sensing driven by deep learning[25].

    (a) The schematic diagram of working principle of intelligent electromagnetic sensing (b) The schematic diagram of intelligent electromagnetic sensing system based on 1-bit information metamaterial (c) Optical images of different human targets and corresponding imaging results (d) The beam focusing on interested human local posture based on intelligent sensing system (e) The sign language recognition results of 10 English letters based on intelligent sensing system (f) The recognition results of respiratory characteristics for two persons based on intelligent perception system

    图  5  数据获取和处理一体化的智能电磁感知成像原理图[28]

    (a)基于1比特信息超材料智能电磁感知的工作原理示意图 (b)和(c)算法原理示意图

    Figure  5.  The schematic diagram of intelligent electromagnetic sensing integrated with data acquisition and processing[28]

    (a) The schematic diagram of working principle of intelligent electromagnetic sensing based on 1-bit information metamaterial (b) and (c) The schematic diagram of proposed algorithm

    图  6  数据采集与处理一体化的智能感知的部分结果[25]

    Figure  6.  Some results of intelligent sensing integrated with data acquisition and processing[25]

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出版历程
  • 收稿日期:  2021-04-15
  • 修回日期:  2021-04-27
  • 网络出版日期:  2021-04-30
  • 刊出日期:  2021-04-28

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