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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Shallow Water Depth Retrieval From Multitemporal Sentinel-1 SAR Data
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Shallow Water Depth Retrieval From Multitemporal Sentinel-1 SAR Data

机译：从多时相Sentinel-1 SAR数据中提取浅水深度

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摘要

The Sentinel-1 constellation can provide numerous high-resolutionnCn-band synthetic aperture radar (SAR) data with long-term continuity and freely, thus showing a cost-effective solution for the coastal monitoring at high or moderate spatial resolutions. The major goal is to improve estimates of shallow water depth for SAR applications. We present an algorithm that is based on the linear dispersion relation between water depth and swell parameters like swell wavelength, direction, and period to estimate shallow water depth using multitemporal SAR data with a short repeating cycle. This is accomplished via circular convolution and Kalman filter that provides both the estimates and a measure of their uncertainty at each location. The introduced algorithm is tested on four Sentinel-1 interferometric wide swath (IW) mode SAR images over the coastal region of Fujian Province, China. The retrieved water depth both from multitemporal SAR images and different single SAR images show general agreement with water depth from an official electronic navigational chart. All comparisons indicate that the proposed method is feasible and multitemporal SAR data have great potential in bathymetric surveying.
机译：Sentinel-1星座图可以提供许多高分辨率n C波段n波段合成孔径雷达（SAR）数据具有长期连续性并且可以自由使用，因此为以高或中等空间分辨率进行海岸监测提供了一种经济高效的解决方案。主要目标是为SAR应用改进对浅水深度的估计。我们提出了一种算法，该算法基于水深与膨胀参数（例如膨胀波长，方向和周期）之间的线性分散关系，使用具有短重复周期的多时相SAR数据来估算浅水深度。这是通过圆形卷积和卡尔曼滤波器完成的，该滤波器同时提供估计值和每个位置不确定性的度量。该算法在福建省沿海地区的四张Sentinel-1干涉宽幅（IW）模式SAR图像上进行了测试。从多时相SAR图像和不同的单个SAR图像中检索到的水深都与官方电子航海图中的水深大体一致。所有的比较表明，该方法是可行的，多时相SAR数据在测深中具有很大的潜力。

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