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Ocean Surface Current Inversion Method for a Doppler Scatterometer.

Authors :
Bao, Qingliu
Lin, Mingsen
Zhang, Youguang
Dong, Xiaolong
Lang, Shuyan
Gong, Peng
Source :
IEEE Transactions on Geoscience & Remote Sensing. Nov2017, Vol. 55 Issue 11, p6505-6516. 12p.
Publication Year :
2017

Abstract

The ocean surface current is a very important parameter of ocean dynamic environment. It is connected to global climate change, marine environment forecasting, marine navigation, engineering security, and so on. The observation and prediction of ocean surface current have attracted more and more concern. Doppler Scatterometer (DopScat) is a new type of radar for ocean surface wind and current field remote sensing. The ocean surface current inversion method of DopScat impacts the measurement accuracy directly. In this paper, we establish the simulation model of a DopScat and provide the radial velocity error model. The numerical ocean surface Doppler spectrum model is also introduced and validated with the empirical geophysical model function in C-band (CDOP). The suitable ocean wave elevation spectrum and directional distribution function are selected. What is more, this paper establishes the maximum likelihood estimation (MLE) method to retrieve the ocean surface current and wind simultaneously. The retrieval accuracy for different positions in cross track, different wind speeds, and different current speeds are analyzed. At last, the global ocean current field is observed by DopScat and the ocean current is retrieved. In our simulation, the orbit parameters and observation geometry of DopScat are the same as that of HY-2A scatterometer. The retrieval results show that global current speed standard deviation can be smaller than 0.18 m/s for five days and 0.5 ^\circ \times 0.5 ^\circ grid average. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
01962892
Volume :
55
Issue :
11
Database :
Academic Search Index
Journal :
IEEE Transactions on Geoscience & Remote Sensing
Publication Type :
Academic Journal
Accession number :
125952158
Full Text :
https://doi.org/10.1109/TGRS.2017.2728824