Estimation of significant wave height from X-band marine radar images

2010 ◽  
Author(s):  
Feng Wang ◽  
Jian Wang ◽  
Shujuan Wang
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Significant Wave ◽  
Radar Images ◽  
X Band ◽  
Marine Radar

Significant wave height estimation using SVR algorithms and shadowing information from simulated and real measured X-band radar images of the sea surface

2015 ◽  
Vol 101 ◽  
pp. 244-253 ◽  
Author(s):  
S. Salcedo-Sanz ◽  
J.C. Nieto Borge ◽  
L. Carro-Calvo ◽  
L. Cuadra ◽  
K. Hessner ◽  
...  
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Sea Surface ◽  
Height Estimation ◽  
Significant Wave ◽  
Radar Images ◽  
X Band

A new method to retrieve significant wave height from X-band marine radar image sequences

2014 ◽  
Vol 35 (11-12) ◽  
pp. 4559-4571 ◽  
Author(s):  
Zhongbiao Chen ◽  
Yijun He ◽  
Biao Zhang ◽  
Zhongfeng Qiu ◽  
Baoshu Yin
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Image Sequences ◽  
New Method ◽  
Radar Image ◽  
Significant Wave ◽  
X Band ◽  
Marine Radar

scholarly journals Wave Height Estimation from Shipborne X-Band Nautical Radar Images

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Xinlong Liu ◽  
Weimin Huang ◽  
Eric W. Gill
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Control Process ◽  
Shadow Image ◽  
Data Quality Control ◽  
Surface Slope ◽  
Significant Wave ◽  
Radar Images ◽  
X Band ◽  
Quality Control Process

A shadowing-analysis-based algorithm is modified to estimate significant wave height from shipborne X-band nautical radar images. Shadowed areas are first extracted from the image through edge detection. Smith’s function fit is then applied to illumination ratios to derive the root mean square (RMS) surface slope. From the RMS surface slope and the mean wave period, the significant wave height is estimated. A data quality control process is implemented to exclude rain-contaminated and low-backscatter images. A smoothing scheme is applied to the gray scale intensity histogram of edge pixels to improve the accuracy of the shadow threshold determination. Rather than a single full shadow image, a time sequence of shadow image subareas surrounding the upwind direction is used to calculate the average RMS surface slope. It has been found that the wave height retrieved from the modified algorithm is underestimated under rain and storm conditions and overestimated for cases with low wind speed. The modified method produces promising results by comparing radar-derived wave heights with buoy data, and the RMS difference is found be 0.59 m.

scholarly journals Estimation of the Significant Wave Height from Marine Radar Images without External Reference

2019 ◽  
Vol 7 (12) ◽  
pp. 432 ◽  
Author(s):  
Ludeno ◽  
Serafino
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
State Monitoring ◽  
Sea State ◽  
Significant Wave ◽  
Radar Images ◽  
External Reference ◽  
Challenging Tasks ◽  
In Situ Sensors ◽  
Marine Radar

In the context of the sea state monitoring by means of the X-band marine radar, the estimation of a significant wave height (Hs) is, currently, one of the most challenging tasks. For its estimation, a calibration is usually required using an external reference, such as in situ sensors, and mainly buoys. In this paper, a method that allows us to avoid the need for an external reference for Hs estimation is presented. This strategy is, mainly, based on the correlation between a raw radar image and the corresponding non-calibrated wave elevation image to which varying its amplitude by using a scale factor creates a mathematical model for the radar imaging. The proposed strategy has been validated by considering a simulated waves field, generated at varying sea state conditions. The results show a good estimation of the significant wave height, confirmed by a squared correlation coefficient greater than 0.70 for each considered sea state.

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