WIND AMBIGUITY REMOVAL BY THE USE OF NEURAL NETWORK TECHNIQUES

被引：22

作者：

BADRAN, F

THIRIA, S

CREPON, M

机构：

[1] UNIV PARIS 06, OCEANOG DYNAM & CLIMATOL LAB, F-75252 PARIS 05, FRANCE

[2] CEDRIC, CONSERVATOIRE NATL ARTS & METIERS, PARIS, FRANCE

来源：

JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS | 1991年 / 96卷 / C11期

关键词：

D O I：

10.1029/91JC02216

中图分类号：

P7 [海洋学];

学科分类号：

0707 ;

摘要：

This paper deals with the removal of ambiguities existing on the direction of the wind measured by satellite scatterometers. It is shown that neural networks are well adapted to solving this problem. Results using ERS.1 simulated scatterometric wind fields are presented. It is found that 99%, of the ambiguities can be removed by imposing a rate of 25% ambiguity at 180-degrees and 90-degrees.

引用

页码：20521 / 20529

页数：9

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