Laser reflective tomography imaging projection registration method based on target contour auto-correction
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1.State Key Laboratory of Pulsed Power Laser Technology, National University of Defense Technology,Hefei 230037, China;2.Advanced Laser Technology Laboratory of Anhui Province, National University of Defense Technology,Hefei 230037, China;3.Anhui Province Key Laboratory of Electronic Restriction, National University of Defense Technology,Hefei 230037, China

Clc Number:

O439

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Supported by the National Natural Science Foundation of China (61871389, 62205372) ; Research Plan Project of the National University of Defense Technology (ZK18-01-02) ; National Defense Science and Technology Innovation Special Zone project (22-TQ23-07-ZD-01-001); Postgraduate Scientific Research Innovation Project of Hunan Province (CX20220007)

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    Abstract:

    Laser reflective tomography imaging has a wide application prospect of space target remote sensing because its resolution is independent of distance. Before the reconstruction of the target image, the multi-angle echoes projection data need to be aligned with the rotation center of the target, which is the projection registration technique. This paper proposed a projection registration method based on the target contour auto-correction, and the experimental results show that the method is easy to implement on simple target since the registration center of rotation, can effectively reduce the number of laser pulses launch and detector receive random jitter caused by the interference, such as solved the problem of the fuzzy image, is a kind of LRTI multi-angle echoes registration of new ideas.

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ZHANG Xin-Yuan, HU Yi-Hua, HAN Fei, SHI Liang, XU Shi-Long, CHEN You-Long, WANG Yi-Cheng. 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

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History
  • Received:October 27,2022
  • Revised:April 13,2023
  • Adopted:November 15,2022
  • Online: March 30,2023
  • Published:
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