蒙特卡罗模拟方法在偏振信息处理中的应用

IF 2.9 4区 工程技术 Q1 MULTIDISCIPLINARY SCIENCES
Haojie Ding, Xiaopeng Gao, Renbin Zhang, Zhongyi Guo
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引用次数: 0

摘要

蒙特卡罗(MC)模拟方法是一种基于采样的方法,用于对不确定性进行量化和传播,广泛应用于散射介质系统中光偏振的散射模拟。本文首先对MC原理和偏振信息进行了简要介绍。随后,深入介绍和分析了MC方法在均匀色散系统、非均匀色散系统和微表面系统下偏振信息处理(PIP)过程中的作用,包括模拟光传输、研究光偏振、探索散射机制、验证实验模型和协助实验结果解释。此外,本文还分析了当前MC模拟方法的不足,并为开发具有成本效益的MC系统提供了建议。综上所述,本文对MC方法在PIP中的研究进展进行了全面的综述。强调了MC方法在复杂环境下偏振探测和偏振成像的强大应用潜力,为未来技术的发展提供了有价值的指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Monte Carlo Simulation Method for Applications of Polarization Information Processing
Monte Carlo (MC) simulation method, a sampling‐based approach used for quantification and propagation of uncertainties, is widely used in scattering simulation of light polarization in scattering media systems. In this review, first, the MC principles and polarization information are briefly introduced. Subsequently, the role of the MC method is introduced and analyzed thoroughly in the process of polarization information processing (PIP) under homogeneous dispersion system, inhomogeneous dispersion system and microsurface system respectively, which includes simulating light transmission, studying light polarization, exploring scattering mechanisms, verifying experimental model and assisting interpretation of experimental results. In addition, this review analyzes the shortcomings of the current MC simulation methods and provides suggestions for the development of cost‐effective MC systems. In summary, this work provides a comprehensive review of the research progress of the MC method in the PIP. It highlights the strong potential applications of the MC method for the polarization detection and polarization imaging in complex environments, which gives valuable guidance for developments of future technology.
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来源期刊
Advanced Theory and Simulations
Advanced Theory and Simulations Multidisciplinary-Multidisciplinary
CiteScore
5.50
自引率
3.00%
发文量
221
期刊介绍: Advanced Theory and Simulations is an interdisciplinary, international, English-language journal that publishes high-quality scientific results focusing on the development and application of theoretical methods, modeling and simulation approaches in all natural science and medicine areas, including: materials, chemistry, condensed matter physics engineering, energy life science, biology, medicine atmospheric/environmental science, climate science planetary science, astronomy, cosmology method development, numerical methods, statistics
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