A unified C-band and Ku-band geophysical model function determined by neural network approach-中国期刊网

摘要 Thegeophysicalmodelfunction(GMF)describestherelationshipbetweenbackscatteringandseasurfacewind,sothatwindvectorscanberetrievedfrombackscatteringmeasurement.TheGMFplaysanimportantroleinoceanwindvectorretrievals,itsperformancewilldirectlyinfluencetheaccuracyoftheretrievedwindvector.Neuralnetwork(NN)approachisusedtodevelopaunifiedGMFforC-bandandKu-band(NN-GMF).EmpiricalGMFCMOD4andQSCAT-1areusedtogeneratethesimulatedtrainingdata-set,andGaussiannoiseatasignalnoiseratioof30dBisaddedtothedata-settosimulatethenoiseinthebackscatteringmeasurement.TheNN-GMFemploysradiofrequencyasanadditionalparameter,soitcanbeappliedforbothC-bandandKu-band.Analysesshowthattheσ0predictedbytheNN-GMFiscomparablewiththeσ0predictedbyCMOD4andQSCAT-1.AlsothewindvectorsretrievedfromtheNN-GMFandempiricalGMFCMOD4andQSCAT-1arecomparable,indicatingthattheNN-GMFisaseffectiveastheempiricalGMF,andhastheadvantagesoftheuniversalform.

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A unified C-band and Ku-band geophysical model function determined by neural network approach

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A unified C-band and Ku-band geophysical model function determined by neural network approach

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