Volume 14 Issue 3
Jun.  2025
Turn off MathJax
Article Contents
Article Navigation >  Journal of Radars  > 2025  >  14(3): 501-527
GUO Yulin, HU Yihua, FANG Jiajie, et al. Research status and development trend of LiDAR super-resolution imaging technology[J]. Journal of Radars, 2025, 14(3): 501–527. doi: 10.12000/JR25028
Citation: GUO Yulin, HU Yihua, FANG Jiajie, et al. Research status and development trend of LiDAR super-resolution imaging technology[J]. Journal of Radars, 2025, 14(3): 501–527. doi: 10.12000/JR25028
shu

Research Status and Development Trend of LiDAR Super-resolution Imaging Technology

DOI: 10.12000/JR25028 CSTR: 32380.14.JR25028
  • 1.

    Advanced Laser Technology Laboratory of Anhui Province, National University of Defense Technology, Hefei 230037, China

  • 2.

    Anhui Province Key Laboratory of Electronic Restriction, National University of Defense Technology, Hefei 230037, China

  • 3.

    Information Security Research Center, Hefei Comprehensive National Science Center, Hefei 230037, China

  • 4.

    Hangzhou Institute for Advanced Study, School of Physics and Optoclectronic Engincering, Hangzhou 310024, China

Funds:  The National Natural Science Foundation of China (61871389), The Scientific Research Project of National University of Defense Technology (24-ZZCX-JDZ-43, 22-ZZCX-07), The Youth Independent Innovation Science Fundation Project of National University of Defense Technology (ZK23-45)
More Information
  • Corresponding author: HU Yihua, skl_hyh@163.com; ZHANG Xinyuan, skl_zxy@163.com
  • Received Date: 2025-02-14
  • Rev Recd Date: 2025-05-09
    • Available Online: 2025-05-22
  • Publish Date: 2025-05-29
    Abstract
  • With the expansion of China’s space interests and the growth in the scale of on-orbit assets, high-precision detection of dark and weak targets in noncooperative space has become the core bottleneck in space security defense and debris removal. Traditional optical or radar detection technologies are limited by diffraction limit and signal-to-noise ratio constraints, and the detection and identification accuracy of “fast, far, small, and dark” targets is insufficient. Light Detection and Ranging (LiDAR), with its high precision and anti-jamming advantages, has gradually become the core technical means of accurately detecting space targets. Technologies such as sub-pixel scanning, synthetic aperture, and reflective tomography enable long-range super-resolution imaging by breaking through the physical limitations of conventional LiDAR systems. This paper begins by summarizing and sorting the critical problems associated with LiDAR super-resolution technology. The key technological research progress is then reported, typical experimental systems and experimental results are analyzed, and the characteristics, advantages, and shortcomings of each system are described with respect to requirements of space exploration, remote sensing, and mapping missions. Finally, the application prospects and development trends are presented.

     

    • FullText(HTML)
  • loading
    • References(121)
  • [1]
    王锋, 张哲, 叶昊, 等. 国外空间态势感知能力分析与发展趋势(特邀)[J]. 激光与光电子学进展, 2024, 61(20): 2011006. doi: 10.3788/LOP240882.

    WANG Feng, ZHANG Zhe, YE Hao, et al. Development status and trends of foreign space situation awareness ability (invited)[J]. Laser & Optoelectronics Progress, 2024, 61(20): 2011006. doi: 10.3788/LOP240882.
    [2]
    马宝林, 朱旭宇. 国外太空态势感知系统发展综述[J]. 战术导弹技术, 2025(1): 60–66, 74. doi: 10.16358/j.issn.1009-1300.20240030.

    MA Baolin and ZHU Xuyu. Development overview of foreign space situation awareness system[J]. Tactical Missile Technology, 2025(1): 60–66, 74. doi: 10.16358/j.issn.1009-1300.20240030.
    [3]
    郑珍珍, 朱振才, 康一舟. 天基空间碎片可见光观测系统与关键技术发展概述[J]. 光学学报, 2022, 42(17): 1712002. doi: 10.3788/AOS202242.1712002.

    ZHENG Zhenzhen, ZHU Zhencai, and KANG Yizhou. Overview of space-based optical observation systems for space debris and development of key technologies[J]. Acta Optica Sinica, 2022, 42(17): 1712002. doi: 10.3788/AOS202242.1712002.
    [4]
    周程灏, 王治乐, 朱峰. 大口径光学合成孔径成像技术发展现状[J]. 中国光学, 2017, 10(1): 25–38. doi: 10.3788/CO.20171001.0025.

    ZHOU Chenghao, WANG Zhile, and ZHU Feng. Review on optical synthetic aperture imaging technique[J]. Chinese Optics, 2017, 10(1): 25–38. doi: 10.3788/CO.20171001.0025.
    [5]
    胡以华, 张鑫源, 徐世龙, 等. 激光反射层析成像技术的研究进展[J]. 中国激光, 2021, 48(4): 0401002. doi: 10.3788/CJL202148.0401002.

    HU Yihua, ZHANG Xinyuan, XU Shilong, et al. Research progress of laser reflective tomography techniques[J]. Chinese Journal of Lasers, 2021, 48(4): 0401002. doi: 10.3788/CJL202148.0401002.
    [6]
    KARR T J. Synthetic aperture Ladar for high-resolution ground-based imaging of objects in LEO, GEO, and Cis-Lunar space[J]. IEEE Transactions on Aerospace and Electronic Systems, 2024, 60(4): 5499–5514. doi: 10.1109/TAES.2024.3396417.
    [7]
    胡以华. 激光成像目标侦察[M]. 北京: 国防工业出版社, 2013.

    HU Yihua. Laser Imaging Target Reconnaissance[M]. Beijing: National Defense Industry Press, 2013.
    [8]
    黎正平. 远距离单光子三维成像的技术研究[D]. [博士论文], 中国科学技术大学, 2020. doi: 10.27517/d.cnki.gzkju.2020.000418.

    LI Zhengping. Long range single-photon three-dimensional imaging[D]. [Ph.D. dissertation], University of Science and Technology of China, 2020. doi: 10.27517/d.cnki.gzkju.2020.000418.
    [9]
    康岩, 薛瑞凯, 李力飞, 等. 基于像素复用的SPAD阵列连续扫描三维成像[J]. 红外与激光工程, 2020, 49(S2): 20200375. doi: 10.3788/IRLA20200375.

    KANG Yan, XUE Ruikai, LI Lifei, et al. Continuous scanning 3D imaging with SPAD array based on pixel multiplexing[J]. Infrared and Laser Engineering, 2020, 49(S2): 20200375. doi: 10.3788/IRLA20200375.
    [10]
    胡以华, 赵禄达. 激光成像处理技术研究现状及展望(特邀)[J]. 红外与激光工程, 2023, 52(6): 20230169. doi: 10.3788/IRLA20230169.

    HU Yihua and ZHAO Luda. Recent progress and prospect of laser imaging processing technology (invited)[J]. Infrared and Laser Engineering, 2023, 52(6): 20230169. doi: 10.3788/IRLA20230169.
    [11]
    张汉熠, 赵新宇, 张益成, 等. 单光子激光雷达研究进展[J]. 中国激光, 2022, 49(19): 1910003. doi: 10.3788/CJL202249.1910003.

    ZHANG Hanyi, ZHAO Xinyu, ZHANG Yicheng, et al. Review of advances in single-photon LiDAR[J]. Chinese Journal of Lasers, 2022, 49(19): 1910003. doi: 10.3788/CJL202249.1910003.
    [12]
    赵浴阳, 周鹏飞, 解天鹏, 等. 单光子激光雷达技术发展现状与趋势[J]. 光电工程, 2024, 51(3): 240037. doi: 10.12086/oee.2024.240037.

    ZHAO Yuyang, ZHOU Pengfei, XIE Tianpeng, et al. Development status and trends of single-photon LiDAR technology[J]. Opto-Electronic Engineering, 2024, 51(3): 240037. doi: 10.12086/oee.2024.240037.
    [13]
    何光辉, 王虹, 方强, 等. 山地坡度自适应星载光子计数激光雷达点云去噪方法[J]. 红外与毫米波学报, 2023, 42(2): 250–259. doi: 10.11972/j.issn.1001-9014.2023.02.016.

    HE Guanghui, WANG Hong, FANG Qiang, et al. Spaceborne photon counting LiDAR point cloud denoising method with the adaptive mountain slope[J]. Journal of Infrared and Millimeter Waves, 2023, 42(2): 250–259. doi: 10.11972/j.issn.1001-9014.2023.02.016.
    [14]
    ZHANG Huang, WANG Changshuo, YU Long, et al. PointGT: A method for point-cloud classification and segmentation based on local geometric transformation[J]. IEEE Transactions on Multimedia, 2024, 26: 8052–8062. doi: 10.1109/TMM.2024.3374580.
    [15]
    赵禄达, 胡以华, 赵楠翔, 等. LiDAR点云深度学习模型的压缩和部署加速方法研究现状与展望(特邀)[J]. 激光与光电子学进展, 2024, 61(20): 2011005. doi: 10.3788/LOP241166.

    ZHAO Luda, HU Yihua, ZHAO Nanxiang, et al. Review of model compression and accelerated development for deep learning in LiDAR point cloud processing (invited)[J]. Laser & Optoelectronics Progress, 2024, 61(20): 2011005. doi: 10.3788/LOP241166.
    [16]
    VUTHEA V and TOSHIYOSHI H. A design of Risley scanner for LiDAR applications[C]. 2018 International Conference on Optical MEMS and Nanophotonics (OMN), Lausanne, Switzerland, 2018: 1–2. doi: 10.1109/OMN.2018.8454641.
    [17]
    RAJ T, HASHIM F H, HUDDIN A B, et al. A survey on LiDAR scanning mechanisms[J]. Electronics, 2020, 9(5): 741. doi: 10.3390/electronics9050741.
    [18]
    ZHOU Jingkun and QIAN Keyuan. Low-voltage wide-field-of-view lidar scanning system based on a MEMS mirror[J]. Applied Optics, 2019, 58(5): A283. doi: 10.1364/AO.58.00A283.
    [19]
    陈敬业, 时尧成. 固态激光雷达研究进展[J]. 光电工程, 2019, 46(7): 190218. doi: 10.12086/oee.2019.190218.

    CHEN Jingye and SHI Yaocheng. Research progress in solid-state LiDAR[J]. Opto-Electronic Engineering, 2019, 46(7): 190218. doi: 10.12086/oee.2019.190218.
    [20]
    赵中民, 习友宝. 三维激光扫描系统的固有误差校正算法[J]. 激光与红外, 2016, 46(1): 34–38. doi: 10.3969/j.issn.1001-5078.2016.01.006.

    ZHAO Zhongmin and XI Youbao. Inherent error correction algorithm for 3D laser scanning system[J]. Laser & Infrared, 2016, 46(1): 34–38. doi: 10.3969/j.issn.1001-5078.2016.01.006.
    [21]
    丁宇韬, 张军, 郭遥, 等. 振镜扫描枕形畸变分析及校正算法[J]. 激光与光电子学进展, 2024, 61(13): 1308001. doi: 10.3788/LOP231782.

    DING Yutao, ZHANG Jun, GUO Yao, et al. Analysis and correction algorithm of pincushion distortion in galvanometer scanning[J]. Laser & Optoelectronics Progress, 2024, 61(13): 1308001. doi: 10.3788/LOP231782.
    [22]
    WANG Dingkang, WATKINS C, and XIE Huikai. MEMS mirrors for LiDAR: A review[J]. Micromachines, 2020, 11(5): 456. doi: 10.3390/mi11050456.
    [23]
    KASTURI A, MILANOVIC V, LOVELL D, et al. Comparison of MEMS mirror LiDAR architectures[C]. MOEMS and Miniaturized Systems XIX, San Francisco, United States, 2020: 112930B. doi: 10.1117/12.2556248.
    [24]
    LI Zhengping, HUANG Xin, CAO Yuan, et al. Single-photon computational 3D imaging at 45 km[J]. Photonics Research, 2020, 8(9): 1532–1540. doi: 10.1364/PRJ.390091.
    [25]
    LI Zhengping, YE Juntian, HUANG Xin, et al. Single-photon imaging over 200 km[J]. Optica, 2021, 8(3): 344. doi: 10.1364/OPTICA.408657.
    [26]
    刘英见, 刘航宇, 蒋凯, 等. 全天候工作单光子计数激光雷达[J]. 光通信研究, 2024(4): 23005001. doi: 10.13756/j.gtxyj.2024.230050.

    LIU Yingjian, LIU Hangyu, JIANG Kai, et al. All-weather single-photon LiDAR[J]. Study on Optical Communications, 2024(4): 23005001. doi: 10.13756/j.gtxyj.2024.230050.
    [27]
    黄远建, 李晓银, 叶文怡, 等. 基于共聚焦亚像素扫描的高分辨三维成像[J]. 光学学报, 2023, 43(8): 822014. doi: 10.3788/AOS221974.

    HUANG Yuanjian, LI Xiaoyin, YE Wenyi, et al. High resolution 3D imaging based on confocal sub-pixel scanning[J]. Acta Optica Sinica, 2023, 43(8): 0822014. doi: 10.3788/AOS221974.
    [28]
    AULL B F, DUERR E K, FRECHETTE J P, et al. Large-format Geiger-Mode avalanche photodiode arrays and readout circuits[J]. IEEE Journal of Selected Topics in Quantum Electronics, 2018, 24(2): 3800510. doi: 10.1109/JSTQE.2017.2736440.
    [29]
    BIAN Liheng, SONG Haoze, PENG Lintao, et al. High-resolution single-photon imaging with physics-informed deep learning[J]. Nature Communications, 2023, 14(1): 5902. doi: 10.1038/s41467-023-41597-9.
    [30]
    CHANG J, LOS J W N, TENORIO-PEARL J O, et al. Detecting telecom single photons with ( ${99.5_{-2.07}^{+0.5}}$) \% system detection efficiency and high time resolution[J]. APL Photonics, 2021, 6(3): 36114. doi: 10.1063/5.0039772.
    [31]
    CHILES J, CHARAEV I, LASENBY R, et al. New constraints on dark photon dark matter with superconducting nanowire detectors in an optical haloscope[J]. Physical Review Letters, 2022, 128(23): 231802. doi: 10.1103/PhysRevLett.128.231802.
    [32]
    KORZH B, ZHAO Qingyuan, ALLMARAS J P, et al. Demonstration of sub-3 ps temporal resolution with a superconducting nanowire single-photon detector[J]. Nature Photonics, 2020, 14(4): 250–255. doi: 10.1038/s41566-020-0589-x.
    [33]
    MCCARTHY A, TAYLOR G G, GARCIA-ARMENTA J, et al. High-resolution long-distance depth imaging LiDAR with ultra-low timing jitter superconducting nanowire single-photon detectors[J]. Optica, 2025, 12(2): 168. doi: 10.1364/OPTICA.544877.
    [34]
    MA Ruoyan, GUO Zhimin, CHEN Dai, et al. Drone-based superconducting nanowire single-photon detection system with a detection efficiency of more than 90%[J]. Advanced Photonics Nexus, 2025, 4(2): 026003. doi: 10.1117/1.APN.4.2.026003.
    [35]
    KIRMANI A, VENKATRAMAN D, SHIN D, et al. First-photon imaging[J]. Science, 2014, 343(6166): 58–61. doi: 10.1126/science.1246775.
    [36]
    SHIN D, KIRMANI A, GOYAL V K, et al. Photon-efficient computational 3-D and reflectivity imaging with single-photon detectors[J]. IEEE Transactions on Computational Imaging, 2015, 1(2): 112–125. doi: 10.1109/TCI.2015.2453093.
    [37]
    SHIN D, SHAPIRO J H, and GOYAL V K. Performance analysis of low-flux least-squares single-pixel imaging[J]. IEEE Signal Processing Letters, 2016, 23(12): 1756–1760. doi: 10.1109/LSP.2016.2617329.
    [38]
    RAPP J and GOYAL V K. A few photons among many: Unmixing signal and noise for photon-efficient active imaging[J]. IEEE Transactions on Computational Imaging, 2017, 3(3): 445–459. doi: 10.1109/TCI.2017.2706028.
    [39]
    ALTMANN Y, REN Ximing, MCCARTHY A, et al. Lidar waveform-based analysis of depth images constructed using sparse single-photon data[J]. IEEE Transactions on Image Processing, 2016, 25(5): 1935–1946. doi: 10.1109/TIP.2016.2526784.
    [40]
    LINDELL D B, O’TOOLE M, and WETZSTEIN G. Single-photon 3D imaging with deep sensor fusion[J]. ACM Transactions on Graphics, 2018, 37(4): 113. doi: 10.1145/3197517.3201316.
    [41]
    PENG Jiayong, XIONG Zhiwei, HUANG Xin, et al. Photon-efficient 3D imaging with a non-local neural network[C]. 16th European Conference on Computer Vision, Glasgow, UK, 2020: 225–241. doi: 10.1007/978-3-030-58539-6_14.
    [42]
    MARINO R M and DAVIS W R JR. Jigsaw: A foliage-penetrating 3D imaging laser radar system[J]. Lincoln Laboratory Journal, 2005, 15(1): 23–36.
    [43]
    MCCARTHY A, REN Ximing, FRERA A D, et al. Kilometer-range depth imaging at 1550 nm wavelength using an InGaAs/InP single-photon avalanche diode detector[J]. Optics Express, 2013, 21(19): 22098. doi: 10.1364/OE.21.022098.
    [44]
    PAWLIKOWSKA A M, HALIMI A, LAMB R A, et al. Single-photon three-dimensional imaging at up to 10 kilometers range[J]. Optics Express, 2017, 25(10): 11919. doi: 10.1364/OE.25.011919.
    [45]
    HONG Yu, LIU Shijie, LI Zhengping, et al. Airborne single-photon LiDAR towards a small-sized and low-power payload[J]. Optica, 2024, 11(5): 612. doi: 10.1364/OPTICA.518999.
    [46]
    KANG Yan, LI Lifei, LIU Dawei, et al. Fast long-range photon counting depth imaging with sparse single-photon data[J]. IEEE Photonics Journal, 2018, 10(3): 1–10. doi: 10.1109/JPHOT.2018.2840681.
    [47]
    郭静菁, 费晓燕, 葛鹏, 等. 基于全光纤光子计数激光雷达的高分辨率三维成像[J]. 红外与激光工程, 2021, 50(7): 20210162. doi: 10.3788/IRLA20210162.

    GUO Jingjing, FEI Xiaoyan, GE Peng, et al. High-resolution three-dimensional imaging based on all-fiber photon-counting Lidar system[J]. Infrared and Laser Engineering, 2021, 50(7): 20210162. doi: 10.3788/IRLA20210162.
    [48]
    邓云凯, 禹卫东, 张衡, 等. 未来星载SAR技术发展趋势[J]. 雷达学报, 2020, 9(1): 1–33. doi: 10.12000/JR20008.

    DENG Yunkai, YU Weidong, ZHANG Heng, et al. Forthcoming spaceborne SAR development[J]. Journal of Radars, 2020, 9(1): 1–33. doi: 10.12000/JR20008.
    [49]
    刘立人. 高分辨率遥感新途径——合成孔径激光成像雷达[J]. 科学, 2014, 66(6): 25–29. doi: 10.3969/j.issn.0368-6396.2014.06.006.

    LIU Liren. A new way to high-resolution remote sensing: Synthetic aperture imaging Ladar[J]. Science, 2014, 66(6): 25–29. doi: 10.3969/j.issn.0368-6396.2014.06.006.
    [50]
    吴谨. 关于合成孔径激光雷达成像研究[J]. 雷达学报, 2012, 1(4): 353–360. doi: 10.3724/SP.J.1300.2012.20076.

    WU Jin. On the development of synthetic aperture Ladar imaging[J]. Journal of Radars, 2012, 1(4): 353–360. doi: 10.3724/SP.J.1300.2012.20076.
    [51]
    徐晨, 晋凯, 魏凯. 合成孔径激光雷达成像技术研究进展[J]. 光电工程, 2024, 51(3): 240007. doi: 10.12086/oee.2024.240007.

    XU Chen, JIN Kai, and WEI Kai. Research progress of synthetic aperture Ladar techniques[J]. Opto-Electronic Engineering, 2024, 51(3): 240007. doi: 10.12086/oee.2024.240007.
    [52]
    LUCKE R L, RICKARD L J, BASHKANSKY M, et al. Synthetic Aperture Ladar (SAL): Fundamental theory, design equations for a satellite system, and laboratory demonstration[R]. NRL/FR/7218--02-10,051, 2002. doi: 10.21236/ADA409859.
    [53]
    张珂殊, 潘洁, 王然, 等. 大幅宽激光合成孔径雷达成像技术研究[J]. 雷达学报, 2017, 6(1): 1–10. doi: 10.12000/JR16152.

    ZHANG Keshu, PAN Jie, WANG Ran, et al. Study of wide swath synthetic aperture Ladar imaging technology[J]. Journal of Radars, 2017, 6(1): 1–10. doi: 10.12000/JR16152.
    [54]
    GAO Shuang, O’SULLIVAN M, and HUI Rongqing. Complex-optical-field lidar system for range and vector velocity measurement[J]. Optics Express, 2012, 20(23): 25867. doi: 10.1364/OE.20.025867.
    [55]
    LU Zhaoyu, YANG Tianxin, LI Zhiyong, et al. Broadband linearly chirped light source with narrow linewidth based on external modulation[J]. Optics Letters, 2018, 43(17): 4144. doi: 10.1364/OL.43.004144.
    [56]
    卢炤宇, 葛春风, 王肇颖, 等. 频率调制连续波激光雷达技术基础与研究进展[J]. 光电工程, 2019, 46(7): 190038. doi: 10.12086/oee.2019.190038.

    LU Zhaoyu, GE Chunfeng, WANG Zhaoying, et al. Basics and developments of frequency modulation continuous wave LiDAR[J]. Opto-Electronic Engineering, 2019, 46(7): 190038. doi: 10.12086/oee.2019.190038.
    [57]
    胡烜, 李道京, 赵绪锋. 基于本振数字延时的合成孔径激光雷达信号相干性保持方法[J]. 中国激光, 2018, 45(5): 0510003. doi: 10.3788/CJL201845.0510003.

    HU Xuan, LI Daojing, and ZHAO Xufeng. Maintaining method of signal coherence in synthetic aperture Ladar based on local oscillator digital delay[J]. Chinese Journal of Lasers, 2018, 45(5): 0510003. doi: 10.3788/CJL201845.0510003.
    [58]
    KE Jiayi, SONG Ziqi, CUI Zhongming, et al. Phase noise compensation experiment with frequency modulated continuous wave laser in atmospheric propagation[J]. Optical Engineering, 2022, 61(7): 073101. doi: 10.1117/1.OE.61.7.073101.
    [59]
    张洁, 王然, 张珂殊. 相位梯度自聚焦算法在合成孔径激光雷达中的应用与改进[J]. 激光与光电子学进展, 2016, 53(6): 062801. doi: 10.3788/LOP53.062801.

    ZHANG Jie, WANG Ran, and ZHANG Keshu. Application and improvement of phase gradient autofocus algorithm in synthetic aperture LiDAR[J]. Laser & Optoelectronics Progress, 2016, 53(6): 062801. doi: 10.3788/LOP53.062801.
    [60]
    XUE Jiyu, CAO Yunhua, WU Zhensen, et al. Inverse synthetic aperture lidar imaging and compensation in slant atmospheric turbulence with phase gradient algorithm compensation[J]. Optics & Laser Technology, 2022, 154: 108329. doi: 10.1016/j.optlastec.2022.10832.
    [61]
    GATT P, JACOB D, BRADFORD B, et al. Performance bounds of the phase gradient autofocus algorithm for synthetic aperture Ladar[C]. Laser Radar Technology and Applications XIV, Orlando, USA, 2009: 73230P. doi: 10.1117/12.822216.
    [62]
    SONG Z, MO D, LI B, et al. Phase gradient matrix autofocus for ISAL space-time-varied phase error correction[J]. IEEE Photonics Technology Letters, 2020, 32(6): 353–356. doi: 10.1109/LPT.2020.2974505.
    [63]
    阮航, 吴彦鸿, 叶伟, 等. 逆合成孔径激光雷达相位误差补偿算法[J]. 激光与光电子学进展, 2013, 50(10): 102801. doi: 10.3788/LOP50.102801.

    RUAN Hang, WU Yanhong, YE Wei, et al. Phase error compensation algorithm for inverse synthetic aperture Ladar[J]. Laser & Optoelectronics Progress, 2013, 50(10): 102801. doi: 10.3788/lop50.102801. doi: 10.3788/LOP50.102801.
    [64]
    刘立人. 直视合成孔径激光成像雷达原理[J]. 光学学报, 2012, 32(9): 0928002. doi: 10.3788/AOS201232.0928002.

    LIU Liren. Principle of down-looking synthetic aperture imaging Ladar[J]. Acta Optica Sinica, 2012, 32(9): 0928002. doi: 10.3788/AOS201232.0928002.
    [65]
    马萌, 李道京, 杜剑波. 振动条件下机载合成孔径激光雷达成像处理[J]. 雷达学报, 2014, 3(5): 591–602. doi: 10.3724/SP.J.1300.2014.13132.

    MA Meng, LI Daojing, and DU Jianbo. Imaging of airborne synthetic aperture Ladar under platform vibration condition[J]. Journal of Radars, 2014, 3(5): 591–602. doi: 10.3724/SP.J.1300.2014.13132.
    [66]
    杜剑波, 李道京, 马萌, 等. 基于干涉处理的机载合成孔径激光雷达振动估计和成像[J]. 中国激光, 2016, 43(9): 0910031. doi: 10.3788/CJL201643.0910003.

    DU Jianbo, LI Daojing, MA Meng, et al. Vibration estimation and imaging of airborne synthetic aperture Ladar based on interferometry processing[J]. Chinese Journal of Lasers, 2016, 43(9): 0910031. doi: 10.3788/CJL201643.0910003.
    [67]
    ZHOU Kai, LI Daojing, GAO Jinghan, et al. Vibration phases estimation based on orthogonal interferometry of inner view field for ISAL imaging and detection[J]. Applied Optics, 2023, 62(11): 2845. doi: 10.1364/AO.481186.
    [68]
    唐禹, 秦宝, 晏芸, 等. 多发多收合成孔径激光雷达高分辨率宽测绘带成像[J]. 红外与激光工程, 2016, 45(8): 0830001. doi: 10.3788/IRLA201645.0830001.

    TANG Yu, QIN Bao, YAN Yun, et al. High-resolution and wide-swath imaging of multiple-transmitter-multiple-receiver synthetic aperture Ladar[J]. Infrared and Laser Engineering, 2016, 45(8): 0830001. doi: 10.3788/IRLA201645.0830001.
    [69]
    张波, 周煜, 孙建锋, 等. 多通道宽幅度合成孔径激光成像雷达收发装置优化研究[J]. 光学学报, 2018, 38(5): 0528002. doi: 10.3788/AOS201838.0528002.

    ZHANG Bo, ZHOU Yu, SUN Jianfeng, et al. Optimization research on multi-channel wide-swath synthetic aperture imaging Ladar transceiver system[J]. Acta Optica Sinica, 2018, 38(5): 0528002. doi: 10.3788/AOS201838.0528002.
    [70]
    李道京, 胡烜. 合成孔径激光雷达光学系统和作用距离分析[J]. 雷达学报, 2018, 7(2): 263–274. doi: 10.12000/JR18017.

    LI Daojing and HU Xuan. Optical system and detection range analysis of synthetic aperture Ladar[J]. Journal of Radars, 2018, 7(2): 263–274. doi: 10.12000/JR18017.
    [71]
    李道京, 周凯, 崔岸婧, 等. 多通道逆合成孔径激光雷达成像探测技术和实验研究[J]. 激光与光电子学进展, 2021, 58(18): 1811017. doi: 10.3788/LOP202158.1811017.

    LI Daojing, ZHOU Kai, CUI Anjing, et al. Multi-channel inverse synthetic aperture Ladar imaging detection technology and experimental research[J]. Laser & Optoelectronics Progress, 2021, 58(18): 1811017. doi: 10.3788/LOP202158.1811017.
    [72]
    汪丙南, 赵娟莹, 李威, 等. 阵列激光合成孔径雷达高分辨成像技术研究[J]. 雷达学报, 2022, 11(6): 1110–1118. doi: 10.12000/JR22204.

    WANG Bingnan, ZHAO Juanying, LI Wei, et al. Array synthetic aperture Ladar with high spatial resolution technology[J]. Journal of Radars, 2022, 11(6): 1110–1118. doi: 10.12000/JR22204.
    [73]
    KIM T, NGAI T, TIMALSINA Y, et al. A single-chip optical phased array in a wafer-scale silicon photonics/CMOS 3D-integration platform[J]. IEEE Journal of Solid-State Circuits, 2019, 54(11): 3061–3074. doi: 10.1109/JSSC.2019.2934601.
    [74]
    CUI Anjing, LI Daojing, WU Jiang, et al. Laser synthetic aperture coherent imaging for micro-rotating objects based on array detectors[J]. IEEE Photonics Journal, 2022, 14(6): 1–9. doi: 10.1109/JPHOT.2022.3225468.
    [75]
    PELLIZZARI C J, TRAHAN R, ZHOU Hanying, et al. Synthetic aperature Ladar: A model-based approach[J]. IEEE Transactions on Computational Imaging, 2017, 3(4): 901–916. doi: 10.1109/TCI.2017.2663320.
    [76]
    徐晨, 宋岸鹏, 晋凯, 等. 改进的基于光学成像模型的逆合成孔径激光雷达成像算法[J]. 激光与光电子学进展, 2023, 60(12): 1228001. doi: 10.3788/LOP221548.

    XU Chen, SONG Anpeng, JIN Kai, et al. Modified imaging algorithm for inverse synthetic aperture LiDAR based on optical imaging model[J]. Laser & Optoelectronics Progress, 2023, 60(12): 1228001. doi: 10.3788/LOP221548.
    [77]
    KRAUSE B W, BUCK J, RYAN C, et al. Synthetic aperture Ladar flight demonstration[C]. CLEO: 2011 - Laser Science to Photonic Applications, Baltimore, USA: IEEE, 2011: 1–2.
    [78]
    卢智勇, 周煜, 孙建峰, 等. 机载直视合成孔径激光成像雷达外场及飞行实验[J]. 中国激光, 2017, 44(1): 0110001. doi: 10.3788/CJL201744.0110001.

    LU Zhiyong, ZHOU Yu, SUN Jianfeng, et al. Airborne down-looking synthetic aperture imaging Ladar field experiment and its flight testing[J]. Chinese Journal of Lasers, 2017, 44(1): 0110001. doi: 10.3788/CJL201744.0110001.
    [79]
    李光远, 卢智勇, 周煜, 等. 直视逆合成孔径激光成像雷达外场实验[J]. 光学学报, 2018, 38(4): 0401001. doi: 10.3788/AOS201838.0401001.

    LI Guangyuan, LU Zhiyong, ZHOU Yu, et al. Outdoor experiment of down-looking inverse synthetic aperture imaging Lidar[J]. Acta Optica Sinica, 2018, 38(4): 0401001. doi: 10.3788/AOS201838.0401001.
    [80]
    张珂殊, 李光祚, 王然, 等. 机载激光合成孔径雷达研究[C]. 第四届高分辨率对地观测学术年会, 武汉, 2017.

    ZHANG Keshu, LI Guangzuo, WANG Ran, et al. The study on airborne laser synthetic aperture radar[C]. The 4th China High Resolution Earth Observation Conference, Wuhan, China, 2017.
    [81]
    MO Di, WANG Ran, WANG Ning, et al. Experiment of inverse synthetic aperture Ladar on real target[C]. 2017 7th IEEE International Conference on Electronics Information and Emergency Communication (ICEIEC), Macau, China, 2017: 319–321. doi: 10.1109/ICEIEC.2017.8076572.
    [82]
    高敬涵, 李道京, 周凯, 等. 衍射光学系统激光雷达接收波束展宽及作用距离分析[J]. 中国激光, 2023, 50(5): 510001. doi: 10.3788/CJL220658.

    GAO Jinghan, LI Daojing, ZHOU Kai, et al. Analysis of receiving beam broadening and detection range of LiDAR based on diffractive optical system[J]. Chinese Journal of Lasers, 2023, 50(5): 510001. doi: 10.3788/CJL220658.
    [83]
    GAO Jinghan, LI Daojing, ZHOU Kai, et al. Imaging and detection method for low signal-to-noise ratio airborne synthetic aperture Ladar signals[J]. Optical Engineering, 2023, 62(9): 098104. doi: 10.1117/1.OE.62.9.098104.
    [84]
    吴谨, 默迪, 梁小虎, 等. 合成孔径激光雷达首次实现百公里距离毫米级方位向分辨率成像[J]. 中国激光, 2025, 52(3): 316003. doi: 10.3788/CJL241393.

    WU Jin, MO Di, LIANG Xiaohu, et al. Hundred-kilometer distance millimeter-level azimuth resolution imaging of synthetic aperture Ladar is first achieved[J]. Chinese Journal of Lasers, 2025, 52(3): 316003. doi: 10.3788/CJL241393.
    [85]
    KALENDER W A. Computed Tomography: Fundamentals, System Technology, Image Quality, Applications[M]. Wiley-VCH, 2006.
    [86]
    HANES S A, BENHAM V N, LASCHE J B, et al. Field demonstration and characterization of a 10.6-μm reflection tomography imaging system[C]. Atmospheric Propagation, Adaptive Systems, and Laser Radar Technology for Remote Sensing, Barcelona, Spain, 2001.
    [87]
    李道京, 高敬涵, 崔岸婧, 等. 成像探测相干激光雷达技术研究进展[J]. 现代雷达, 2023, 45(11): 1–6. doi: 10.16592/j.cnki.1004-7859.2023.11.001.

    LI Daojing, GAO Jinghan, CUI Anjing, et al. Research progress of coherent Ladar technology for imaging and detection[J]. Modern Radar, 2023, 45(11): 1–6. doi: 10.16592/j.cnki.1004-7859.2023.11.001.
    [88]
    JIN Xiaofeng, SUN Jianfeng, YAN Yi, et al. Application of phase retrieval algorithm in reflective tomography laser radar imaging[J]. Chinese Optics Letters, 2011, 9(1): 012801. doi: 10.3788/COL20110901.12801.
    [89]
    赵楠翔, 胡以华. 激光反射层析成像相位恢复算法研究[J]. 红外与激光工程, 2019, 48(10): 1005005. doi: 10.3788/IRLA201948.1005005.

    ZHAO Nanxiang and HU Yihua. Research of phase retrieval algorithm in laser reflective tomography imaging[J]. Infrared and Laser Engineering, 2019, 48(10): 1005005. doi: 10.3788/IRLA201948.1005005.
    [90]
    周德力, 黄庚华, 石亮, 等. 非合目标的激光反射层析投影配准方法[J]. 科学技术与工程, 2014, 14(21): 104–107, 112. doi: 10.3969/j.issn.1671-1815.2014.21.018.

    ZHOU Deli, HUANG Genghua, SHI Liang, et al. Laser reflective tomography projection registration method of non-cooperative target[J]. Science Technology and Engineering, 2014, 14(21): 104–107, 112. doi: 10.3969/j.issn.1671-1815.2014.21.018.
    [91]
    杨彪, 胡以华, 林放. 激光反射层析断层成像恢复方法[J]. 光子学报, 2018, 47(4): 0407001. doi: 10.3788/gzxb20184704.0407001.

    YANG Biao, HU Yihua, and LIN Fang. Research of phase retrieval method in laser reflective tomography imaging[J]. Acta Photonica Sinica, 2018, 47(4): 0407001. doi: 10.3788/gzxb20184704.0407001.
    [92]
    WANG Jincheng, ZHOU Shiwei, SHI Liang, et al. Image quality analysis and improvement of Ladar reflective tomography for space object recognition[J]. Optics Communications, 2016, 359: 177–183. doi: 10.1016/j.optcom.2015.09.069.
    [93]
    谷雨, 胡以华, 郝士琦, 等. 变分贝叶斯解卷积法在激光反射层析成像中的应用[J]. 光学学报, 2016, 36(6): 0611003. doi: 10.3788/AOS201636.0611003.

    GU Yu, HU Yihua, HAO Shiqi, et al. Application of variational Bayesian deconvolution method in laser reflective tomography imaging[J]. Acta Optica Sinica, 2016, 36(6): 0611003. doi: 10.3788/AOS201636.0611003.
    [94]
    林放, 王金诚, 张华, 等. 多帧迭代盲解卷积在激光反射断层成像的应用[J]. 光学学报, 2017, 37(9): 0911001. doi: 10.3788/AOS201737.0911001.

    LIN Fang, WANG Jincheng, ZHANG Hua, et al. Application of multi-frame iterative blind deconvolution method in laser reflective tomography imaging[J]. Acta Optica Sinica, 2017, 37(9): 0911001. doi: 10.3788/AOS201737.0911001.
    [95]
    陆新飞, 夏洁, 尹治平, 等. 基于两维解卷积和稀疏回波去噪的高分辨雷达成像方法[J]. 雷达学报, 2018, 7(3): 285–293. doi: 10.12000/JR17108.

    LU Xinfei, XIA Jie, YIN Zhiping, et al. High-resolution radar imaging using 2D deconvolution with sparse echo denoising[J]. Journal of Radars, 2018, 7(3): 285–293. doi: 10.12000/JR17108.
    [96]
    谷雨, 胡以华, 郝士琦, 等. 激光反射层析成像中滤波反投影算法特性研究[J]. 激光与红外, 2015, 45(12): 1500–1504. doi: 10.3969/j.issn.1001--5078.2015.12.018.

    GU Yu, HU Yihua, HAO Shiqi, et al. Study on influence of filter back-projection on laser reflective tomography[J]. Laser & Infrared, 2015, 45(12): 1500–1504. doi: 10.3969/j.issn.1001--5078.2015.12.018.
    [97]
    张鑫源. 反射层析激光雷达成像关键技术研究[D]. [博士论文], 国防科技大学, 2023.

    ZHANG Xinyuan. Key technologies research on reflective tomography Lidar imaging[D]. [Ph.D. dissertation], National University of Defense Technology, 2023.
    [98]
    MURRAY J, TRISCARI J, FETZER G, et al. Tomographic lidar[C]. Lasers, Sources and Related Photonic Devices, San Diego, USA, 2010: LSWA1. doi: 10.1364/LSC.2010.LSWA1.
    [99]
    KNIGHT F K, KULKARNI S R, MARINO R M, et al. Tomographic techniques applied to laser radar reflective measurements[J]. The Lincoln Laboratory Journal, 1989, 2: 143–160.
    [100]
    LI Xianyu, HE Yulin, and HUA Qun. Application of computed tomographic image reconstruction algorithms based on filtered back-projection in diagnosis of bone trauma diseases[J]. Journal of Medical Imaging and Health Informatics, 2020, 10(5): 1219–1224. doi: 10.1166/jmihi.2020.3036.
    [101]
    杨彪, 胡以华. 代数迭代法在激光反射断层成像目标重构中的应用[J]. 红外与激光工程, 2019, 48(7): 0726002. doi: 10.3788/IRLA201948.0726002.

    YANG Biao and HU Yihua. Laser reflection tomography target reconstruction algorithm based on algebraic iteration[J]. Infrared and Laser Engineering, 2019, 48(7): 0726002. doi: 10.3788/IRLA201948.0726002.
    [102]
    GUO Rui, JIANG Zheyi, JIN Zhihan, et al. Reflective tomography lidar image reconstruction for long distance non-cooperative target[J]. Remote Sensing, 2022, 14(14): 3310. doi: 10.3390/rs14143310.
    [103]
    HU Dianlin, LIU Jin, LV Tianling, et al. Hybrid-domain neural network processing for sparse-view CT reconstruction[J]. IEEE Transactions on Radiation and Plasma Medical Sciences, 2021, 5(1): 88–98. doi: 10.1109/TRPMS.2020.3011413.
    [104]
    GUO Fupei, YANG Bo, FENG Hao, et al. An efficient sinogram domain fully convolutional interpolation network for sparse-view computed tomography reconstruction[J]. Applied Sciences, 2023, 13(20): 11264. doi: 10.3390/app132011264.
    [105]
    LEE H, LEE J, KIM H, et al. Deep-neural-network-based sinogram synthesis for sparse-view CT image reconstruction[J]. IEEE Transactions on Radiation and Plasma Medical Sciences, 2019, 3(2): 109–119. doi: 10.1109/TRPMS.2018.2867611.
    [106]
    刘一凡, 胡以华, 徐世龙, 等. 基于波形分解的激光反射层析成像优化方法[J]. 光学学报, 2023, 43(18): 1828002. doi: 10.3788/AOS222044.

    LIU Yifan, HU Yihua, XU Shilong, et al. Optimization method for laser reflective tomography imaging based on waveform decomposition[J]. Acta Optica Sinica, 2023, 43(18): 1828002. doi: 10.3788/AOS222044.
    [107]
    ZHANG Xinyuan, HAN Fei, SHEN Shiyang, et al. Target region extraction and segmentation algorithm for reflective tomography lidar image[J]. IET Image Processing, 2023, 17(4): 1001–1009. doi: 10.1049/ipr2.12691.
    [108]
    张鑫源, 胡以华, 谌诗洋, 等. 公里级激光反射层析实验和碎片质心估计[J]. 物理学报, 2022, 71(11): 114205. doi: 10.7498/aps.71.20220205.

    ZHANG Xinyuan, HU Yihua, SHEN Shiyang, et al. Kilometer-level laser reflective tomography experiment and debris barycenter estimation[J]. Acta Physica Sinica, 2022, 71(11): 114205. doi: 10.7498/aps.71.20220205.
    [109]
    苗清然, 王海霞, 于洋, 等. 光学相干层析成像在指尖生物特征识别中的应用[J]. 激光与光电子学进展, 2023, 60(8): 0811012. doi: 10.3788/LOP230484.

    MIAO Qingran, WANG Haixia, YU Yang, et al. Application of optical coherence tomography in fingertip biometrics[J]. Laser & Optoelectronics Progress, 2023, 60(8): 0811012. doi: 10.3788/LOP230484.
    [110]
    INDUMATHI R and VASUKI R. Segmentation and feature extraction in lung CT images with deep learning model architecture[J]. SN Computer Science, 2023, 4(5): 552. doi: 10.1007/s42979-023-01892-0.
    [111]
    PARKER J K, CRAIG E B, KLICK D I, et al. Reflective tomography: Images from range-resolved laser radar measurements[J]. Applied Optics, 1988, 27(13): 2642–2643. doi: 10.1364/AO.27.002642.
    [112]
    MOSLEY D E, MATSON C L, and CZYZAK S R. Active imaging of space objects using the HI-CLASS (high-performance CO2 Ladar surveillance sensor) laser system[C]. Laser Radar Technology and Applications II, Orlando, USA, 1997: 52–60. doi: 10.1117/12.281036.
    [113]
    MATSON C L and MOSLEY D E. Reflective tomography reconstruction of satellite features—field results[J]. Applied Optics, 2001, 40(14): 2290–2296. doi: 10.1364/AO.40.002290.
    [114]
    MATSON C L, HOLLAND D E, PIERROTTET D F, et al. Satellite feature reconstruction using reflective tomography: Field results[C]. Optics in Atmospheric Propagation and Adaptive Systems II, London, UK, 1998: 65–72. doi: 10.1117/12.298050.
    [115]
    HENRIKSSON M, OLOFSSON T, GRÖNWALL C, et al. Optical reflectance tomography using TCSPC laser radar[C]. Electro-Optical Remote Sensing, Photonic Technologies, and Applications VI, Edinburgh, United Kingdom, 2012: 85420E. doi: 10.1117/12.974493.
    [116]
    陈剑彪, 孙华燕, 孔舒亚, 等. 激光反射层析成像仿真方法研究[J]. 激光与光电子学进展, 2019, 56(13): 131104. doi: 10.3788/LOP56.131104.

    CHEN Jianbiao, SUN Huayan, KONG Shuya, et al. Simulation method of laser reflection tomography imaging[J]. Laser & Optoelectronics Progress, 2019, 56(13): 131104. doi: 10.3788/LOP56.131104.
    [117]
    张鑫源, 胡以华, 韩飞, 等. 基于目标轮廓自动校正的激光反射层析成像投影配准方法[J]. 红外与毫米波学报, 2023, 42(3): 410–417. doi: 10.11972/j.issn.1001-9014.2023.03.017.

    ZHANG Xinyuan, HU Yihua, HAN Fei, et al. Laser reflective tomography imaging projection registration method based on target contour auto-correction[J]. Journal of Infrared and Millimeter Waves, 2023, 42(3): 410–417. doi: 10.11972/j.issn.1001-9014.2023.03.017.
    [118]
    瞿福琪, 胡以华, 焦均均, 等. 星对星激光雷达反射层析成像技术探讨[J]. 光子学报, 2013, 42(1): 48–53. doi: 10.3788/gzxb20134201.0048.

    QU Fuqi, HU Yihua, JIAO Junjun, et al. Satellite-to-satellite lidar imaging using reflective tomography[J]. Acta Photonica Sinica, 2013, 42(1): 48–53. doi: 10.3788/gzxb20134201.0048.
    [119]
    胡以华, 张鑫源, 韩飞, 等. 反射层析激光雷达实现小远目标超分辨成像[J]. 中国激光, 2023, 50(3): 0316003. doi: 10.3788/CJL221519.

    HU Yihua, ZHANG Xinyuan, HAN Fei, et al. Super-resolution imaging of small distant targets by reflective tomography Lidar[J]. Chinese Journal of Lasers, 2023, 50(3): 0316003. doi: 10.3788/CJL221519.
    [120]
    李道京, 胡烜, 周凯, 等. 基于共形衍射光学系统的合成孔径激光雷达成像探测[J]. 光学学报, 2020, 40(4): 0428001. doi: 10.3788/AOS202040.0428001.

    LI Daojing, HU Xuan, ZHOU Kai, et al. Synthetic aperture Lidar imaging detection based on conformal diffractive optical system[J]. Acta Optica Sinica, 2020, 40(4): 0428001. doi: 10.3788/AOS202040.0428001.
    [121]
    杨坚, 马跃, 于文博, 等. 星载单光子激光雷达海洋噪声模型[J]. 红外与毫米波学报, 2024, 43(3): 393–398. doi: 10.11972/j.issn.1001-9014.2024.03.013.

    YANG Jian, MA Yue, YU Wenbo, et al. Noise model of oceanic spaceborne photon counting LiDAR[J]. Journal of Infrared and Millimeter Waves, 2024, 43(3): 393–398. doi: 10.11972/j.issn.1001-9014.2024.03.013.
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Get Citation
    PDF
    XML
    Article views(1262) PDF downloads(300) Cited by()
    Proportional views
    Related

    京ICP备20021838号-14   Supported by: Beijing Renhe Information Technology Co. Ltd     百度统计

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return