Optical Turbulence Profile in Marine Environment with Artificial Neural Network Model

doi:10.3390/rs14092267

	Optical Turbulence Profile in Marine Environment with Artificial Neural Network Model
	Bi, Cuicui 1,2,3; Qing, Chun 2,3; Wu, Pengfei 2,3; Jin, Xiaomei 2,3; Liu, Qing 2,3; Qian, Xianmei 2,3; Zhu, Wenyue 2,3; Weng, Ningquan 2,3
刊名	REMOTE SENSING
	2022-05-01
卷号	14
关键词	atmospheric optics optical turbulence thermosonde balloon-borne genetic algorithm
DOI	10.3390/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.
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关键词	SIMULATIONS ; PARAMETERS ; ATMOSPHERE ; RADIOSONDE ; SLODAR ; SITES ; LAYER
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	MDPI
WOS记录号	WOS:000794732100001
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
内容类型	期刊论文
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.Univ Sci & Technol China, Sci Isl Branch, Grad Sch, Hefei 230026, Peoples R China 2.Adv Laser Technol Lab Anhui Prov, Hefei 230037, Peoples R China 3.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Hefei Inst Phys Sci, Key Lab Atmospher Opt, Hefei 230031, 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).