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

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.