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Multiscale Decomposition Prediction of Propagation Loss in Oceanic Tropospheric Ducts

文献类型：期刊论文

作者Dang, Mingxia3; Wu, Jiaji3; Cui, Shengcheng2; Guo, Xing3; Cao, Yunhua1; Wei, Heli2; Wu, Zhensen1
刊名REMOTE SENSING
出版日期2021-03-01
卷号13
关键词propagation loss in oceanic tropospheric duct prediction nonlinear prediction division-and-conquest strategy artificial neural network optimization
DOI10.3390/rs13061173
通讯作者Wu, Jiaji(wujj@mail.xidian.edu.cn)
英文摘要The oceanic tropospheric duct is a structure with an abnormal atmospheric refractive index. This structure severely affects the remote sensing detection capability of electromagnetic systems designed for an environment with normal atmospheric refraction. The propagation loss of electromagnetic waves in the oceanic duct is an important concept in oceanic duct research. Owing to the long-term stability and short-term irregular changes in marine environmental parameters, the propagation loss in oceanic ducts has nonstationary and multiscale time characteristics. In this paper, we propose a multiscale decomposition prediction method for predicting the propagation loss in oceanic tropospheric ducts. The prediction performance was verified by simulating propagation loss data with noise. Using different evaluation criteria, the experimental results indicated that the proposed method outperforms six other comparison methods. Under noisy conditions, ensemble empirical mode decomposition effectively disassembles the original propagation loss into a limited number of stable sequences with different scale characteristics. Accordingly, predictive modeling was conducted based on multiscale propagation loss characteristic sequences. Finally, we reconstructed the predicted result to obtain the predicted value of the propagation loss in the oceanic duct. Additionally, a genetic algorithm was used to improve the generalization ability of the proposed method while avoiding the nonlinear predictor from falling into a local optimum.
WOS关键词EMPIRICAL MODE DECOMPOSITION ; NEURAL-NETWORK ; EVAPORATION DUCT
资助项目National Natural Science Foundation of China[61775175] ; National Natural Science Foundation of China[61901335] ; National Natural Science Foundation of China[61771378] ; Basic research program of Natural Science Foundation in Shaanxi Province[2020JQ-331]
WOS研究方向Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:000651927400001
出版者MDPI
资助机构National Natural Science Foundation of China ; Basic research program of Natural Science Foundation in Shaanxi Province
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/122143]  
专题中国科学院合肥物质科学研究院
通讯作者Wu, Jiaji
作者单位1.Xidian Univ, Sch Phys & Optoelect Engn, Xian 710071, Peoples R China
2.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Hefei 230031, Peoples R China
3.Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China
推荐引用方式
GB/T 7714		 Dang, Mingxia,Wu, Jiaji,Cui, Shengcheng,et al. Multiscale Decomposition Prediction of Propagation Loss in Oceanic Tropospheric Ducts[J]. REMOTE SENSING,2021,13.
APA Dang, Mingxia.,Wu, Jiaji.,Cui, Shengcheng.,Guo, Xing.,Cao, Yunhua.,...&Wu, Zhensen.(2021).Multiscale Decomposition Prediction of Propagation Loss in Oceanic Tropospheric Ducts.REMOTE SENSING,13.
MLA Dang, Mingxia,et al."Multiscale Decomposition Prediction of Propagation Loss in Oceanic Tropospheric Ducts".REMOTE SENSING 13(2021).

入库方式： OAI收割

来源：合肥物质科学研究院

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