神经网络反演散射计风场算法的研究

宋新改; 林明森; 蒋兴伟

神经网络反演散射计风场算法的研究

1.
中国海洋大学, 山东青岛 266003
2.
中国海洋大学, 山东青岛 266003;国家卫星海洋应用中心, 北京 100081
3.
国家卫星海洋应用中心, 北京 100081

基金项目: 国家高技术研究发展计划(863)资助项目(2004AA639850)

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出版历程
- 收稿日期: 2005-04-15
- 修回日期: 2005-08-18

Neural network wind retrieval from ERS-1/2 scatterometer data

1.
Ocean University of China, Qingdao 266003 China
2.
Ocean University of China, Qingdao 266003 China;National Satellite Ocean Application Service, Beijing 100081, China
3.
National Satellite Ocean Application Service, Beijing 100081, China

摘要

摘要: 建立了一个神经网络反演卫星散射计海面风场的B-P算法,给出了一个神经网络反演风场的模型,并利用该反演算法和模型对实际卫星散射计数据进行了海面风场反演试验,对风向的多解性利用圆中数滤波方法进行排除.对神经网络训练和检验数据集分别采用ERS-1/2散射计数据和欧洲中期天气预报(ECMWF)提供的风场作为配准点数据.把反演的风速和风向与CMCD4和ECMWF的风场作了比较,它们吻合得比较好;研究表明神经网络反演海面风场是可行和高效的.
- B-P网络 /
- 散射计 /
- 风场反演 /
- 模糊消除
Abstract: A neural network methodology is presented to retrieve wind vectors from ERS 1/2 scatterometer data,and resolving directional ambiguities for scatterometer winds are removed by a circular median filter algorithm.Training data set and test data set come from ERS 1/2 scatterometer data collocated pairs with ECMWF vectors.Comparing the inversion wind velocity and wind direction with CMCD 4 and ECM WF wind vector,the result is good,the run speed is quicker than other method.The good per formance of the neural net work method suggest sthat wind retrieval from ERS 1/2 scatter ometer is possible.
- BP-NN /
- scatterometer /
- wind retrieval /
- resolving directional ambiguities

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参考文献(9)

李燕初,孙瀛,林明森,等.用圆中数滤波器排除卫星散射计风场反演中的风向模糊[J].台湾海峡,1999,18:42-48.

GISH H.A probabilistic approach to the understanding and training of neural network classifiers[A].Proc IEEE Int Conf Acoust:Signal Processing(ICASSP)[C].New York:Institute of Electrical and Electronics Engineers,1990.1 361-1 364.

BADRAN F,THIRIA S,CREPON M.Wind ambiguity removal by the use of neural network techniques[J].J G R,1991,96:20 521-20 529.

MEJIA C,THIRIA S,TRAN N,et al.Determination of the geophysical model function of the ERS-1 scatterometer by the use of neural networks[J].J G R,1998,96:12 853-12 868.

MEJIA C,BADRAN F,BENTAMY A,et al.Determination of the geophysical model function of NSCAT and its corresponding variance by the use of neural networks[J].J G R,1999,104:11 539-11 556.

LIN Ming-sen,SUN Ying,ZHENG Shu-qing.A study on a new retrieval algorithm for measurement of oceanic wind vectors field using satellite microwave scatterometer[J].Acta Oceanologica Sinica,1998,17:305-391.

RICHAUME P,BADRAN F,MEJIA C,et al.Neural network wind retrieval from ERS-1 scatterometer data[J].J G R,2000,105(0):8 737-8 751.

THIRIA S,MEJIA C,BADRAN F.A neural network approach for modeling nonlinear transfer functions:application for wind retrieval from spaceborne scatterometer data[J].J G R,1991,96:20 521-20 529.

林明森.一种修正的星载散射计反演海面风场的场方式反演算法.遥感学报,2000,4:61-65.

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