Prediction of laser far-field intensity distribution through passive imaging

He Hao; Qiushi Wang; Jiabin Bai; Hongrui Wang; Shuiliang Zhou

doi:10.1117/12.3057322

5 February 2025 Prediction of laser far-field intensity distribution through passive imaging

He Hao, Qiushi Wang, Jiabin Bai, Hongrui Wang, Shuiliang Zhou

Author Affiliations +

Proceedings Volume 13509, International Conference on Optical and Photonic Engineering (icOPEN 2024); 135091P (2025) https://doi.org/10.1117/12.3057322
Event: International Conference on Optical and Photonic Engineering (icOPEN 2024), 2024, Foshan, China

Abstract

The far-field intensity of lasers is an essential parameter for long-range laser emission, affecting the performance in laser countermeasures, laser imaging, and laser communication, etc. Predicting the laser distribution and power density before actual emission is therefore crucial. During long-distance air transmission, the far-field intensity distribution is influenced by atmospheric factors such as scattering and turbulence. The conventional calculation method utilizes separate visibility and turbulence testing equipment to abstract the current atmospheric conditions into a few parameters, followed by the application of physical formulas or empirical rules to estimate a result, which causes the loss of detailed atmospheric information. This paper presents a novel method for predicting intensity distribution. By performing analysis on the image acquired from the light path of the laser emission system, we can extract the atmospheric factors and predict the laser distribution using deep learning models, thereby avoiding the need for additional equipment and enabling quasi-real-time prediction. Simulation and experiments demonstrate that the new method achieves higher accuracy and has the potential to provide computation results for in-time decision.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

He Hao, Qiushi Wang, Jiabin Bai, Hongrui Wang, and Shuiliang Zhou "Prediction of laser far-field intensity distribution through passive imaging", Proc. SPIE 13509, International Conference on Optical and Photonic Engineering (icOPEN 2024), 135091P (5 February 2025); https://doi.org/10.1117/12.3057322

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