Estimating Significant Wave Height from SAR with Long Integration Times
Source abstract
Abstract
Synthetic aperture radar (SAR) is an important means of estimating significant wave height with obvious advantages of all-day, all-weather, high resolution and wide swath coverage. At present, the estimation methods of significant wave height are based on visible ocean waves in SAR images. However, due to the characteristic of long integration time for low-frequency SAR (such as P-band, L-band), the ocean waves are usually invisible in SAR images. In addition, in the case that there are multiple wave systems, significant wave height of only one wave system can be estimated for the reason that only a blurred wave system can be observed in SAR images. In order to solve the above two problems, a method of estimating significant wave height from SAR with long integration times is proposed in this paper. Firstly, each ocean wave system is refocused from single-look complex (SLC) data, respectively. Then, without any additional processing, the 180° ambiguity of wave propagation direction is removed based on the optimum focus setting. Finally, significant wave height is estimated in combination with azimuth cutoff, wavelength and propagation direction of ocean waves. This method is applied to two airborne SAR field data with long integration times. One case is that ocean waves are invisible in SAR images, the other is that there are two wave systems on the real ocean surface, but only one is visible in the SAR images. The results show that the proposed method can estimate significant wave height in the cases of invisible ocean waves and multiple ocean waves. The estimation results of significant wave height are compared with the European Centre for Medium-Range Weather Forecast (ECMWF) data, and the error is basically stable within 0.2 m, which verifies the effectiveness of the proposed method.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Ocean Waves and Remote Sensing · Oceanographic and Atmospheric Processes · Coastal and Marine Dynamics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
National Key Lab of Microwave Imaging Technology, Beijing 100190, China
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
References (31)
Show source-provided references
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