• Infrared and Laser Engineering
  • Vol. 52, Issue 5, 20220682 (2023)
Rui Wang1,2,3, Bo Liu1,2,3, Zhikang Li1,2,3, Zhen Chen1,2, and Hao Yi1,2,3
Author Affiliations
  • 1Key Laboratory of Science and Technology on Space Optoelectronic Precision Measurement, Chinese Academy of Sciences, Chengdu 610209, China
  • 2Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China
  • 3University of Chinese Academy of Sciences, Beijing 100049, China
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    DOI: 10.3788/IRLA20220682 Cite this Article
    Rui Wang, Bo Liu, Zhikang Li, Zhen Chen, Hao Yi. Adaptive spatial-temporal correlation depth estimation of photon-counting lidar[J]. Infrared and Laser Engineering, 2023, 52(5): 20220682 Copy Citation Text show less
    Echo photon counts model
    Fig. 1. Echo photon counts model
    (a) Overall flow chart; (b) Adaptive selection of the time window
    Fig. 2. (a) Overall flow chart; (b) Adaptive selection of the time window
    Neighborhood data set (3×3). (a) The time interval of the maximum counts of each pixel in the neighborhood; (b) The time interval of the neighborhood data set and the corresponding photon counts in the original histogram
    Fig. 3. Neighborhood data set (3×3). (a) The time interval of the maximum counts of each pixel in the neighborhood; (b) The time interval of the neighborhood data set and the corresponding photon counts in the original histogram
    (a) The original terrain; (b) Photon statistical histogram (M=10000 and 2 MHz noise)
    Fig. 4. (a) The original terrain; (b) Photon statistical histogram (M=10000 and 2 MHz noise)
    Comparison of reconstruction results of different algorithms at different noise intensities. (a) 0.2 MHz noise, 14.3 PPP; (b) 2 MHz noise, 13.8 PPP; (c) 3.5 MHz noise, 14.6 PPP; (d) 6 MHz noise, 14.1 PPP
    Fig. 5. Comparison of reconstruction results of different algorithms at different noise intensities. (a) 0.2 MHz noise, 14.3 PPP; (b) 2 MHz noise, 13.8 PPP; (c) 3.5 MHz noise, 14.6 PPP; (d) 6 MHz noise, 14.1 PPP
    (a) Block diagram of photon counting lidar system; (b) Physical picture of device
    Fig. 6. (a) Block diagram of photon counting lidar system; (b) Physical picture of device
    (a) Visible band image; (b) Reconstructed truth depth image of target
    Fig. 7. (a) Visible band image; (b) Reconstructed truth depth image of target
    Reconstruction results of target. (a) 0.23 MHz noise, 21.6 PPP; (b) 1.21 MHz noise, 21.2 PPP; (c) 2.17 MHz noise, 21.8 PPP; (d) 3.02 MHz noise, 22.5 PPP; (e) 5.08 MHz noise, 23.9 PPP
    Fig. 8. Reconstruction results of target. (a) 0.23 MHz noise, 21.6 PPP; (b) 1.21 MHz noise, 21.2 PPP; (c) 2.17 MHz noise, 21.8 PPP; (d) 3.02 MHz noise, 22.5 PPP; (e) 5.08 MHz noise, 23.9 PPP
    ParameterValue
    Initial time resolution ( $ \mathrm{\tau } $)/ps 400
    Detection time ( $\Delta { { {t} } }$)/ms 0.5
    Dead time $ ({t}_{d} $)/ns 30
    Photon detection efficiency (η) 2.8%
    Number of pulses accumulated (M) 20
    Table 1. The main parameters of the simulated echo data
    Rui Wang, Bo Liu, Zhikang Li, Zhen Chen, Hao Yi. Adaptive spatial-temporal correlation depth estimation of photon-counting lidar[J]. Infrared and Laser Engineering, 2023, 52(5): 20220682
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