Abstract
In the context of the sea state monitoring by means of the X-band marine radar, the estimation of a significant wave height ( H s ) 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 H s 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.
Highlights
X-band marine radar is a useful and well-assessed technology for sea state monitoring for both offshore and coastal areas
Within the last three decades, several algorithms, mainly based on spectral analysis, have been developed in order to retrieve the sea state parameters starting from the raw radar images [1,2,3,4,5,6]
The wave radar system is employed in many applicative scenarios since these algorithms provide accurate measurements of the sea states in terms of the period, length, and direction of the dominant waves, the significant wave height, and the reconstruction of the sea surface current and bathymetry fields [7,8,9,10,11,12,13]
Summary
X-band marine radar is a useful and well-assessed technology for sea state monitoring for both offshore and coastal areas. The wave radar system is employed in many applicative scenarios since these algorithms provide accurate measurements of the sea states in terms of the period, length, and direction of the dominant waves, the significant wave height, and the reconstruction of the sea surface current and bathymetry fields [7,8,9,10,11,12,13]. In this context, one of the most interesting and challenging tasks is the estimation of the significant wave height (Hs). The methods based on spectral analysis [14] or approaches based on time analysis [15,16,17] or other techniques, including an iterative least square approach [18] and a wavelet-based algorithm [19], are recalled
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