Application and Algorithm Design of Multi-Channel Sensor Fusion Technology for Laser Spot Detection

According to the principle, characteristics and use of CCD, this paper designs a laser beam quality measurement program using CCD as a beacon light capture detector and proposes a laser spot detection method based on CCD.The experimental steps and calculation steps for laser beam width measurement and laser power measurement by CCD camera are proposed respectively.The beacon light is used as a light source, and the spot image is processed according to the principle of gray-scale image thresholding to capture the beacon light and present it in the form of a spot on the CCD image sensor.Then, through binarization processing, the spot of the beacon light is distinguished from the background, so as to realize the spot position detection of the beacon light beam.The image data are collected to experimentally detect the laser spot position detection algorithm based on CCD image sensor proposed in this paper, respectively.In the fine-tracking spot position detection, the spot is adjusted in the range of 9.25mrad, and the solution value 1 min is set to be determined every 0.78mrad.The spot center is kept in the range of 9.05mrad, and centering is carried out every 0.003mrad according to the fine-centering algorithm.The experimental results show that the spots after fine centering are all within the range of 0.78mrad, and the change trend is consistent with the simulation results, so the laser spot position detection algorithm proposed in this paper is feasible in fine tracking spot position detection.

Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2025-04-16
DOI
https://doi.org/10.61091/jcmcc127b-050
Primary Topic
Optical Systems and Laser Technology
Type
article
Field-Weighted Citation Impact
0.00

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article

Application and Algorithm Design of Multi-Channel Sensor Fusion Technology for Laser Spot Detection

Journal of Combinatorial Mathematics and Combinatorial Computing
Optical Systems and Laser Technology
article

Application and Algorithm Design of Multi-Channel Sensor Fusion Technology for Laser Spot Detection

article en

Abstract

According to the principle, characteristics and use of CCD, this paper designs a laser beam quality measurement program using CCD as a beacon light capture detector and proposes a laser spot detection method based on CCD.The experimental steps and calculation steps for laser beam width measurement and laser power measurement by CCD camera are proposed respectively.The beacon light is used as a light source, and the spot image is processed according to the principle of gray-scale image thresholding to capture the beacon light and present it in the form of a spot on the CCD image sensor.Then, through binarization processing, the spot of the beacon light is distinguished from the background, so as to realize the spot position detection of the beacon light beam.The image data are collected to experimentally detect the laser spot position detection algorithm based on CCD image sensor proposed in this paper, respectively.In the fine-tracking spot position detection, the spot is adjusted in the range of 9.25mrad, and the solution value 1 min is set to be determined every 0.78mrad.The spot center is kept in the range of 9.05mrad, and centering is carried out every 0.003mrad according to the fine-centering algorithm.The experimental results show that the spots after fine centering are all within the range of 0.78mrad, and the change trend is consistent with the simulation results, so the laser spot position detection algorithm proposed in this paper is feasible in fine tracking spot position detection.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 127b
National Key Research and Development Program of China
Openalex Percentile: Top 94%
Optical Systems and Laser Technology
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Application and Algorithm Design of Multi-Channel Sensor Fusion Technology for Laser Spot Detection · Journal of Combinatorial Mathematics and Combinatorial Computing (2025) | TGRS Research Map | TGRS