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Sea surface wind speed inversion method for Tiangong-2 detection data based on deep learning

A technology of deep learning and sea surface wind speed, which is applied in the field of remote sensing, can solve problems such as the inversion of sea surface wind speed from Tiangong-2 detection data, and achieve the effects of easy implementation, improved accuracy, and high efficiency

Active Publication Date: 2020-11-17
NAT UNIV OF DEFENSE TECH
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Problems solved by technology

However, the retrieval of sea surface wind speed from Tiangong-2 detection data has not yet been realized.

Method used

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  • Sea surface wind speed inversion method for Tiangong-2 detection data based on deep learning
  • Sea surface wind speed inversion method for Tiangong-2 detection data based on deep learning
  • Sea surface wind speed inversion method for Tiangong-2 detection data based on deep learning

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Embodiment Construction

[0025] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.

[0026] The Tiangong-2 imaging altimeter is the first altimeter in the world that uses a small incident angle and a short interference baseline to achieve a wide swath. method. Tiangong-2 imaging height can calculate the image amplitude spectrum, image phase spectrum, image mean value and image variance after receiving the backscatter coefficient reflected from the sea surface. These parameter information are closely related to the sea surface wind speed, and the powerful nonlinear function of the deep neural network can be used to fit the relationship between these parameters and the sea surface wind speed, without the need to study the deep relationship between various physical quantities of t...

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Abstract

The invention discloses a sea surface wind speed inversion method for Tiangong-2 detection data based on deep learning, and the method comprises the following steps: obtaining a back scattering coefficient, an incident angle and image parameters from Tiangong-2 image data, wherein the image parameters comprise an image amplitude spectrum, an image phase spectrum, an image mean value and an image variance; and based on the obtained backscattering coefficient, incident angle and image parameter, calculating to obtain the sea surface wind speed by adopting a preset Tiangong-2 imaging altimeter effective wave height deep learning inversion model. The wide-swath sea surface wind speed inversion of the two-dimensional observation data is realized by utilizing Tiangong-2 detection data.

Description

technical field [0001] The invention belongs to the technical field of remote sensing, and in particular relates to a method for retrieving sea surface wind speed from Tiangong-2 detection data based on deep learning. Background technique [0002] Sea surface wind speed (Wind Speed, WSPD) is an important part of the sea surface wind field, and it is also an important link in exploring the ocean-air interaction in the atmosphere-ocean boundary layer. With the continuous advancement of my country's maritime power strategy, it has become an urgent need to efficiently and accurately obtain sea surface wind speed based on the refined needs of maritime business and support. [0003] There are many ways to measure sea surface wind speed. Among them, based on the measured data of sea surface buoys and survey ships, although the measurement accuracy is high, the measurement range is very limited and cannot meet the needs of practical applications. At present, there are many methods ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/50G06N3/04G06N3/08
CPCG06T5/50G06N3/08G06T2207/10032G06T2207/20056G06T2207/20081G06T2207/20084G06N3/045
Inventor 郭朝刚艾未华刘茂宏乔俊淇
Owner NAT UNIV OF DEFENSE TECH
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