Advanced Imaging, Volume. 2, Issue 5, 051002(2025)

Super-resolution imaging using reflective tomography LiDAR over 10 km

Xinyuan Zhang1,2,3, Leqi Shan1,2, Jiajie Fang1,2, Rui Guo4, Shilong Xu1,2, Yicheng Wang1,2, Yulin Guo1,2, Xing Yang1,2, Fei Han1,2、*, and Yihua Hu1,2、*
Author Affiliations
  • 1State Key Laboratory of Pulsed Power Laser Technology, National University of Defense Technology, Hefei, China
  • 2Advanced Laser Technology Laboratory of Anhui Province, Electronic Engineering Institute, National University of Defense Technology, Hefei, China
  • 3Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China
  • 4School of Automation, Northwestern Polytechnical University, Xi’an, China
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    Figures & Tables(10)
    Schematic of RTL projection.
    Schematic of the RTL system. CM, concave mirror; EOM, electro-optic modulator; AOM, acousto-optic modulator; P, polarizer; M, mirror; NL, negative lens; Nd:YAG, neodymium-doped yttrium-aluminum-garnet laser; WP, wave plate; ND, neutral density filter; IPC, industrial personal computer; APD, avalanche photodiode; MMF, multimode fiber.
    Layout of the experimental setup. (a) Image of the test tower with a 100-mm-aperture telescope. (b) The target is fixed at an angle of 30° with the direction of light rotating on a rotary table. (c) The RTL system.
    (a) Image of two plates fixed on a translation stage. (b) Image of a plate (300 mm×200 mm) fixed on a precise rotating platform. (c) Echo waveforms of two plates with different spacing distances, i.e., 23, 25, 27, and 35 mm, over 10 km. (d) Echo waveforms of one plate (300 mm×200 mm) with different rotation angles, i.e., 0°, 10°, 20°, and 30°, over 10 km.
    (a) Projection data of WordArt target. Projections were taken at 1° intervals from 0° (one side forward) to 180° (another side forward). (b) Image reconstructed by the FBP algorithm with measured data. (c) Typical feature dimensions of the target.
    (a) Image reconstructed by the FBP algorithm with ROIs. (b) MTF curves of ROIs.
    (a) Equally sampled projection data with an interval of 5°. (b) Randomly sampled projection data with a sampling rate the same as the 5° uniform sampling. (c) Equally sampled projection data with an interval of 10°. (b) Randomly sampled projection data with a sampling rate the same as the 10° uniform sampling.
    Reconstruction results of fully and sparsely sampled data using the FBP algorithm, ART, and NLM algorithm.
    Evaluation of reconstruction performance using the metric (a) IE, (b) CC, (c) PSNR, and (d) SSIM. The reference image of the evaluation is a detailed and sharp image of the model.
    • Table 1. Key Parameters of the RTL System.

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      Table 1. Key Parameters of the RTL System.

       ParameterValue
      Laser
      Wavelength (nm)1064
      Full width at half-maximum pulse width (ps)>63
      Pulse energy (mJ)<75
      Pulse repetition rate (Hz)15
      Beam diameter (mm)8.5
      Beam divergence (mrad)0.7
      Expander
      Expanding times3.5
      Beam divergence (mrad)0.2
      Aperture (mm)31.5
      Telescope
      Aperture (mm)260
      Focal length (mm)1000
      Field of view (mrad)0.0625
      Optical efficiency>95%
      Receiver
      3  dB bandwidth, APD (GHz)7.5
      Avalanche gain>100
      Gigabit samples per second (GHz)50
      Trigger
      Bandwidth (GHz)>10
      Active area diameter (μm)32
      Rise time/Fall time (ps)<25/<25
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    Xinyuan Zhang, Leqi Shan, Jiajie Fang, Rui Guo, Shilong Xu, Yicheng Wang, Yulin Guo, Xing Yang, Fei Han, Yihua Hu, "Super-resolution imaging using reflective tomography LiDAR over 10 km," Adv. Imaging 2, 051002 (2025)

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    Paper Information

    Category: Research Article

    Received: Jun. 10, 2025

    Accepted: Aug. 5, 2025

    Published Online: Sep. 2, 2025

    The Author Email: Fei Han (feihan@ustc.edu.cn), Yihua Hu (skl_hyh@163.com)

    DOI:10.3788/AI.2025.10013

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