Estimate of significant wave height from non-coherent marine radar images by multilayer perceptrons

Abstract

One of the most relevant parameters to characterize the severity of ocean waves is the significant wave height (H s ). The estimate of H s from remotely sensed data acquired by non-coherent X-band marine radars is a problem not completely solved nowadays. A method commonly used in the literature (standard method) uses the square root of the signal-to-noise ratio (SNR) to linearly estimate H s . This method has been widely used during the last decade, but it presents some limitations, especially when swell-dominated sea states are present. To overcome these limitations, a new non-linear method incorporating additional sea state information is proposed in this article. This method is based on artificial neural networks (ANNs), specifically on multilayer perceptrons (MLPs). The information incorporated in the proposed MLP-based method is given by the wave monitoring system (WaMoS II) and concerns not only to the square root of the SNR, as in the standard method, but also to the peak wave length and mean wave period. Results for two different platforms (Ekofisk and FINO 1) placed in different locations of the North Sea are presented to analyze whether the proposed method works regardless of the sea states observed in each location or not. The obtained results empirically demonstrate how the proposed non-linear solution outperforms the standard method regardless of the environmental conditions (platform), maintaining real-time properties.

Proof of Feasibility of the Sea State Monitoring from Data Collected in Medium Pulse Mode by a X-Band Wave Radar System

“…Consequently, the medium pulse mode has a low sensitivity for detecting sea state with wave period lower than of 7 s. Before discussing the discrepancy concerning the significant wave height H s , it is worth noticing that the radar image, acquired by the wave monitoring system, is not the direct representation of the sea surface due distortion occurring in the electromagnetic scattering phenomenon. In particular, the intensity of the received signal is mostly related to the electromagnetic backscattering of the sea surface rather than to the sea wave elevation [17,23]. Accordingly, the function F w k x , k y , ω retrieved from the analysis of the radar data represents a "scaled version" of the actual sea wave spectrum.…”

“…So, defining the MTF allows us to mitigate the distortions introduced in the radar imaging process [22][23][24][25]. It worth noting that in this measurement campaign, the same MTF has been adopted for both the working modes.…”

Combined Method for Measuring 3D Wave Spectra. I. Algorithms to Transform the Optical-Brightness Field into the Wave-Height Distribution

“…The indirect methods of obtaining information on wind waves, which are based on processing of the radar (including satellite) or optical images of the sea surface are widely spread. For example, the radar systems are actively used for estimating the average height of the waves and other wave characteristics on vast areas [12][13][14][15].…”

Ocean Wind and Wave Measurements Using X-Band Marine Radar: A Comprehensive Review

“…Under low wind speeds or swell-dominated sea state conditions, the BGN energy may be low, leading to large SNR and, therefore, overestimated H S . Thus, Vicen-Bueno et al [67] proposed a non-linear model using artificial neural networks (ANN) with multilayer perceptrons (MLP) for H S estimation.…”

“…The technique was tested using two datasets [67]. One dataset with 49096 measurements and manifested bimodal (wind sea and swell) sea states was collected at Ekofisk in the Norwegian sector of the North Sea from October, 2008 to May, 2009.…”