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垂直路径大气激光通信中 CN2 轮廓反演的计算模型。

A Computational Model of Cn2 Profile Inversion for Atmospheric Laser Communication in the Vertical Path.

机构信息

Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China.

Key Laboratory of Photoelectric Measurement and Control and Optical Information Transfer Technology of Ministry of Education, Changchun University of Science and Technology, 7089 Weixing Road, Changchun 130022, China.

出版信息

Sensors (Basel). 2023 Jun 25;23(13):5874. doi: 10.3390/s23135874.

DOI:10.3390/s23135874
PMID:37447724
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10347151/
Abstract

In this paper, an atmospheric structure constant Cn2 model is proposed for evaluating the channel turbulence degree of atmospheric laser communication. First, we derive a mathematical model for the correlation between the atmospheric coherence length r0, the isoplanatic angle θ0 and Cn2 using the Hufnagel-Valley (HV) turbulence model. Then, we calculate the seven parameters of the HV model with the actual measured r0 and θ0 data as input quantities, so as to draw the Cn2 profile and the θ0 profile. The experimental results show that the fitted average Cn2 contours and single-day Cn2 contours have superior fitting performance compared with our historical data, and the daily correlation coefficient between the single-day computed θ0 contours and the measured θ0 contours is up to 87%. This result verifies the feasibility of the proposed method. The results validate the feasibility of the proposed method and provide a new technical tool for the inversion of turbulence Cn2 profiles.

摘要

本文提出了一种大气结构常数 Cn2 模型,用于评估大气激光通信信道的湍流程度。首先,我们利用 Hufnagel-Valley(HV)湍流模型推导出大气相干长度 r0、等晕角θ0 和 Cn2 之间的相关数学模型。然后,我们将实际测量的 r0 和θ0 数据作为输入量,计算 HV 模型的七个参数,从而绘制 Cn2 轮廓和θ0 轮廓。实验结果表明,拟合平均 Cn2 轮廓和单日 Cn2 轮廓的性能优于我们的历史数据,单日计算的θ0 轮廓与实测θ0 轮廓之间的日相关系数高达 87%。这一结果验证了所提出方法的可行性。该结果验证了所提出方法的可行性,并为大气湍流 Cn2 剖面的反演提供了一种新的技术工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/1ec269cf4a32/sensors-23-05874-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/0661a8c56731/sensors-23-05874-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/53b045de4b5a/sensors-23-05874-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/249b1ca6a7df/sensors-23-05874-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/5db170769c90/sensors-23-05874-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/9635db36c3cf/sensors-23-05874-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/cac05f9a92e6/sensors-23-05874-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/ef1400e07493/sensors-23-05874-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/1ec269cf4a32/sensors-23-05874-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/0661a8c56731/sensors-23-05874-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/53b045de4b5a/sensors-23-05874-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/249b1ca6a7df/sensors-23-05874-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/5db170769c90/sensors-23-05874-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/9635db36c3cf/sensors-23-05874-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/cac05f9a92e6/sensors-23-05874-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/ef1400e07493/sensors-23-05874-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b58/10347151/1ec269cf4a32/sensors-23-05874-g008.jpg

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本文引用的文献

1
Generation of temporal fading envelope sequences for the FSOC channel based on atmospheric turbulence optical parameters.基于大气湍流光学参数生成用于FSOC信道的时间衰落包络序列。
Opt Express. 2022 Sep 12;30(19):34519-34532. doi: 10.1364/OE.465847.
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