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Optical Turbulence Profile in Marine Environment with Artificial Neural Network Model

文献类型：期刊论文

作者Bi, Cuicui1,2,3; Qing, Chun1,3; Wu, Pengfei1,3; Jin, Xiaomei1,3; Liu, Qing1,3; Qian, Xianmei1,3; Zhu, Wenyue1,3; Weng, Ningquan1,3
刊名REMOTE SENSING
出版日期2022-05-01
卷号14
关键词atmospheric optics optical turbulence thermosonde balloon-borne genetic algorithm
DOI10.3390/rs14092267
通讯作者Qing, Chun(chunqing@aiofm.ac.cn)
英文摘要Optical turbulence strongly affects different types of optoelectronic and adaptive optics systems. Systematic direct measurements of optical turbulence profiles [C-n(2)(h)] are lacking for many climates and seasons, particularly in marine environments, because it is impractical and expensive to deploy instrumentation. Here, a backpropagation neural network optimized using a genetic algorithm (GA-BP) is developed to estimate atmospheric turbulence profiles in marine environments which is validated against corresponding [C-n(2)(h)] profile datasets from a field campaign of balloonborne microthermal measurements at the Haikou marine environment site. Overall, the trend and magnitude of the GA-BP model and measurements agree. The [C-n(2)(h)] profiles from the GA-BP model are generally superior to those obtained by BP and the physically-based (HMNSP99) models. Several statistical operators were used to quantify the GA-BP model performance on reconstructing the optical turbulence profiles in marine environments. The characterization of vertical distributions of optical turbulence profiles and the main integral parameters derived from [C-n(2)(h)] profiles are presented. The median Fried parameter, isoplanatic angle, and coherence time are 9.94 cm, 0.69 '', and 2.85 ms, respectively, providing independent optical turbulence parameters for adaptive optics systems. The proposed approach exhibits potential for implementation in ground-based optical applications in marine environments.
WOS关键词SIMULATIONS ; PARAMETERS ; ATMOSPHERE ; RADIOSONDE ; SLODAR ; SITES ; LAYER
资助项目Foundation of Advanced Laser Technology Laboratory of Anhui Province[AHL2021QN02] ; Foundation of Key Laboratory of Science and Technology Innovation of Chinese Academy of Sciences[CXJJ-21S028]
WOS研究方向Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:000794732100001
出版者MDPI
资助机构Foundation of Advanced Laser Technology Laboratory of Anhui Province ; Foundation of Key Laboratory of Science and Technology Innovation of Chinese Academy of Sciences
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/130847]  
专题中国科学院合肥物质科学研究院
通讯作者Qing, Chun
作者单位1.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Hefei Inst Phys Sci, Key Lab Atmospher Opt, Hefei 230031, Peoples R China
2.Univ Sci & Technol China, Sci Isl Branch, Grad Sch, Hefei 230026, Peoples R China
3.Adv Laser Technol Lab Anhui Prov, Hefei 230037, Peoples R China
推荐引用方式
GB/T 7714		 Bi, Cuicui,Qing, Chun,Wu, Pengfei,et al. Optical Turbulence Profile in Marine Environment with Artificial Neural Network Model[J]. REMOTE SENSING,2022,14.
APA Bi, Cuicui.,Qing, Chun.,Wu, Pengfei.,Jin, Xiaomei.,Liu, Qing.,...&Weng, Ningquan.(2022).Optical Turbulence Profile in Marine Environment with Artificial Neural Network Model.REMOTE SENSING,14.
MLA Bi, Cuicui,et al."Optical Turbulence Profile in Marine Environment with Artificial Neural Network Model".REMOTE SENSING 14(2022).

入库方式： OAI收割

来源：合肥物质科学研究院

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