研究目的
To propose a method for removing the wind direction ambiguity in wind retrieval from SAR images using Along-track Interferometric SAR (ATI-SAR) phase information, without relying on external sources.
研究成果
The proposed method successfully removes the wind direction ambiguity using ATI-SAR phase information, showing good agreement with atmospheric model data and visual inspection. It demonstrates the feasibility of extracting wind direction without external sources, with better performance in uniform wind conditions.
研究不足
The method assumes that the surface velocity is dominated by wind-induced drift and wave motion, which may not hold in very low wind conditions or when the wind has a low radial component. It also assumes the total surface current is within 90 degrees of the wind direction. The spatial resolution of extracted wind vectors is coarser than the original images.
1：Experimental Design and Method Selection:
The study uses ATI-SAR phase to resolve the 180-degree ambiguity in wind direction extracted from SAR intensity images. The method involves processing interferometric phase data and combining it with intensity-based wind direction extraction (Local Gradient method).
2：Sample Selection and Data Sources:
Two TerraSAR-X/TanDEM-X images acquired on August 9 and 20, 2014, in the South-Western Baltic Sea. Wind data from the SMHI-HIRLAM atmospheric model is used for comparison.
3：List of Experimental Equipment and Materials:
TerraSAR-X/TanDEM-X satellite system for SAR data acquisition.
4：Experimental Procedures and Operational Workflow:
SAR intensity images are processed using the Local Gradient method to detect wind streaks and extract ambiguous wind directions. ATI-SAR phase is calibrated and processed to determine the sign of the phase (positive for advancing, negative for receding targets), which is used to resolve the ambiguity. Wind vectors are extracted and compared with model data.
5：Data Analysis Methods:
Statistical analysis of local gradient directions, visual investigation of images, and comparison with atmospheric model data.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
