• Infrared and Laser Engineering
  • Vol. 53, Issue 11, 20240322 (2024)
Jiaxin YU1, Haifeng YAO2,3,*, Zhi LIU4, Weihao WANG1..., Shaoqian TIAN1, Zhongyu CAO4, Keyan DONG4, Shiming GAO5,6 and Fan BAI7|Show fewer author(s)
Author Affiliations
  • 1School of Electronic Information Engineering, Changchun University of Science and Technology, Changchun 130022, China
  • 2School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China
  • 3Changsanjiao Research Institute, Beijing Institute of Technology, Jiaxing 314000, China
  • 4National and Local Joint Engineering Research Center for Space Optoelectronics Technology, Changchun University of Science and Technology, Changchun 130022, China
  • 5Centre for Optical and Electromagnetic Research, State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang University, Hangzhou 310058, China
  • 6Ningbo Innovation Center, Zhejiang University, Ningbo 315100, China
  • 7Beijing Institute of Spacecraft Engineering, Beijing 100094, China
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    DOI: 10.3788/IRLA20240322 Cite this Article
    Jiaxin YU, Haifeng YAO, Zhi LIU, Weihao WANG, Shaoqian TIAN, Zhongyu CAO, Keyan DONG, Shiming GAO, Fan BAI. Extraction method of atmospheric turbulence characteristic parameters for six aperture structure[J]. Infrared and Laser Engineering, 2024, 53(11): 20240322 Copy Citation Text show less
    Schematic diagram of the six-aperture mask device. (a) 3D image; (b) Configuration diagram
    Fig. 1. Schematic diagram of the six-aperture mask device. (a) 3D image; (b) Configuration diagram
    Algorithm process diagram. (a) Original image frame; (b) Image after preprocessing; (c) Image after K-means mean clustering; (d) Image with centroid calibration
    Fig. 2. Algorithm process diagram. (a) Original image frame; (b) Image after preprocessing; (c) Image after K-means mean clustering; (d) Image with centroid calibration
    Spot sticking leads to incorrect center of mass identification
    Fig. 3. Spot sticking leads to incorrect center of mass identification
    Flowchart of K-means clustering algorithm
    Fig. 4. Flowchart of K-means clustering algorithm
    The algorithm identifies the error probability
    Fig. 5. The algorithm identifies the error probability
    Schematic diagram of the experimental system
    Fig. 6. Schematic diagram of the experimental system
    Field communication link and transceiver. (a) Geographic location of the transmitter; (b) Propagation link 865 m; (c) Geographic location of the receiver; (d) Transmitter, light source is 532 nm; (e) Receiver, detector is CMOS
    Fig. 7. Field communication link and transceiver. (a) Geographic location of the transmitter; (b) Propagation link 865 m; (c) Geographic location of the receiver; (d) Transmitter, light source is 532 nm; (e) Receiver, detector is CMOS
    Measurement software design. (a) Software program flow chart ; (b) PC interface
    Fig. 8. Measurement software design. (a) Software program flow chart ; (b) PC interface
    K-means clustering algorithm and threshold segmentation algorithm measurement comparison
    Fig. 9. K-means clustering algorithm and threshold segmentation algorithm measurement comparison
    Daily variation trend of turbulence
    Fig. 10. Daily variation trend of turbulence
    ParameterValue
    LaserWavelength/nm532
    CCDResolution1920 pixel×1920 pixel
    Pixel size5.86 μm×5.86 μm
    Maximum frame rate/frame·s−1168
    Optical antennasEffective caliber/mm80
    Focal length/mm600
    Focal ratio f7.5
    Table 1. Experimental equipment parameters
    Jiaxin YU, Haifeng YAO, Zhi LIU, Weihao WANG, Shaoqian TIAN, Zhongyu CAO, Keyan DONG, Shiming GAO, Fan BAI. Extraction method of atmospheric turbulence characteristic parameters for six aperture structure[J]. Infrared and Laser Engineering, 2024, 53(11): 20240322
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