Ocean Turbulence Observation Techniques and Data Processing Algorithms based on SAR Sequence Images

Waves in the ocean are a widespread phenomenon and their effective detection requires the use of high-resolution, large-area detection devices. Synthetic aperture radar (SAR), with its all-weather performance and high resolution, is often used for the detection and imaging of both land and ocean, as...

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Published inJournal of physics. Conference series Vol. 2565; no. 1; pp. 12011 - 12022
Main Author Xu, Junru
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.08.2023
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ISSN1742-6588
1742-6596
1742-6596
DOI10.1088/1742-6596/2565/1/012011

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Abstract Waves in the ocean are a widespread phenomenon and their effective detection requires the use of high-resolution, large-area detection devices. Synthetic aperture radar (SAR), with its all-weather performance and high resolution, is often used for the detection and imaging of both land and ocean, as well as large-area, high-resolution SAR and interferometric SAR, which are all based on SAR enhancements. This has become an important area of research in marine sensors, and the use of multiple-input multiple-output (MIMO) reception modes for detection and imaging of large-area, high-resolution SAR data has become one of the research priorities for obtaining large-area, high-resolution SAR data. Oceanic internal waves generate internal mixing of seawater through unstable fragmentation, which is an important mechanism for maintaining the meridional overturning circulation within the ocean, and the strong currents and strong mixing processes generated by large amplitude internal waves carry enormous energy. The main objective of this paper is to investigate ocean turbulence observation techniques and data processing algorithms based on SAR sequence images. The research is of great significance for the development of marine science, and the technical areas studied are of great research significance for the development of the marine economy, breakthroughs in marine research technology, and the development of the marine industry.
AbstractList Waves in the ocean are a widespread phenomenon and their effective detection requires the use of high-resolution, large-area detection devices. Synthetic aperture radar (SAR), with its all-weather performance and high resolution, is often used for the detection and imaging of both land and ocean, as well as large-area, high-resolution SAR and interferometric SAR, which are all based on SAR enhancements. This has become an important area of research in marine sensors, and the use of multiple-input multiple-output (MIMO) reception modes for detection and imaging of large-area, high-resolution SAR data has become one of the research priorities for obtaining large-area, high-resolution SAR data. Oceanic internal waves generate internal mixing of seawater through unstable fragmentation, which is an important mechanism for maintaining the meridional overturning circulation within the ocean, and the strong currents and strong mixing processes generated by large amplitude internal waves carry enormous energy. The main objective of this paper is to investigate ocean turbulence observation techniques and data processing algorithms based on SAR sequence images. The research is of great significance for the development of marine science, and the technical areas studied are of great research significance for the development of the marine economy, breakthroughs in marine research technology, and the development of the marine industry.
Author Xu, Junru
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SubjectTerms Algorithms
Data processing
High resolution
Image resolution
Internal waves
Marine technology
Ocean currents
Physics
Radar detection
Seawater
Synthetic aperture radar
Turbulence
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Title Ocean Turbulence Observation Techniques and Data Processing Algorithms based on SAR Sequence Images
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