A Neural Network Method for Inversion of Turbulence Strength

IF 1.4 4区 物理与天体物理 Q2 MATHEMATICS, APPLIED
Weishi Yin, Baoyin Zhang, Pinchao Meng, Linhua Zhou, Dequan Qi
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引用次数: 0

Abstract

Accurate inversion of atmospheric turbulence strength is a challenging problem in modern turbulence research due to its practical significance. Inspired by transfer learning, we propose a new neural network method consisting of convolution and pooling modules for the atmospheric turbulence strength inversion problem. Its input is the intensity image of the beam and its output is the refractive index structure constant characterizing the atmospheric turbulence strength. We evaluate the inversion performance of the neural network at different beams. Meanwhile, to enhance the generalisation of the network, we mix data sets from different turbulence environments to construct new data sets. Additionally, the inverted atmospheric turbulence strength is used as a priori information to help identify turbulent targets. Experimental results demonstrate the effectiveness of our proposed method.

Abstract Image

反演湍流强度的神经网络方法
大气湍流强度的精确反演是现代湍流研究中一个极具挑战性的问题,因为它具有重要的现实意义。受迁移学习的启发,我们针对大气湍流强度反演问题提出了一种由卷积和池化模块组成的新型神经网络方法。它的输入是光束的强度图像,输出是表征大气湍流强度的折射率结构常数。我们评估了神经网络在不同光束下的反演性能。同时,为了增强网络的通用性,我们混合了不同湍流环境的数据集,以构建新的数据集。此外,反演的大气湍流强度被用作先验信息,以帮助识别湍流目标。实验结果证明了我们提出的方法的有效性。
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来源期刊
Journal of Nonlinear Mathematical Physics
Journal of Nonlinear Mathematical Physics PHYSICS, MATHEMATICAL-PHYSICS, MATHEMATICAL
CiteScore
1.60
自引率
0.00%
发文量
67
审稿时长
3 months
期刊介绍: Journal of Nonlinear Mathematical Physics (JNMP) publishes research papers on fundamental mathematical and computational methods in mathematical physics in the form of Letters, Articles, and Review Articles. Journal of Nonlinear Mathematical Physics is a mathematical journal devoted to the publication of research papers concerned with the description, solution, and applications of nonlinear problems in physics and mathematics. The main subjects are: -Nonlinear Equations of Mathematical Physics- Quantum Algebras and Integrability- Discrete Integrable Systems and Discrete Geometry- Applications of Lie Group Theory and Lie Algebras- Non-Commutative Geometry- Super Geometry and Super Integrable System- Integrability and Nonintegrability, Painleve Analysis- Inverse Scattering Method- Geometry of Soliton Equations and Applications of Twistor Theory- Classical and Quantum Many Body Problems- Deformation and Geometric Quantization- Instanton, Monopoles and Gauge Theory- Differential Geometry and Mathematical Physics
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