scholarly journals An Adaptive Method of Wave Spectrum Estimation Using X-Band Nautical Radar

2015 ◽  
Vol 7 (12) ◽  
pp. 16537-16554 ◽  
Author(s):  
Al-Abbass Al-Habashneh ◽  
Cecilia Moloney ◽  
Eric Gill ◽  
Weimin Huang
Keyword(s):  
Wave Spectrum ◽  
Adaptive Method ◽  
Spectrum Estimation ◽  
X Band

scholarly journals The Effect of Radar Ocean Surface Sampling on Wave Spectrum Estimation Using X-Band Marine Radar

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 17570-17585 ◽  
Author(s):  
Al-Abbass Al-Habashneh ◽  
Cecilia Moloney ◽  
Eric W. Gill ◽  
Weimin Huang
Keyword(s):  
Wave Spectrum ◽  
Ocean Surface ◽  
Spectrum Estimation ◽  
Surface Sampling ◽  
X Band ◽  
Marine Radar

Sea State Estimation Based on Ship Motions Measurements and Data Fusion

2013 ◽  
Author(s):  
Céline Drouet ◽  
Nicolas Cellier ◽  
Jérémie Raymond ◽  
Denis Martigny
Keyword(s):  
Data Fusion ◽  
State Estimation ◽  
Wave Height ◽  
Significant Wave Height ◽  
Wave Spectrum ◽  
Ocean Waves ◽  
Ship Motions ◽  
Sea State ◽  
Significant Wave ◽  
X Band

In-service monitoring can help to increase safety of ships especially regarding the fatigue assessment. For this purpose, it is compulsory to know the environmental conditions encountered: wind, but also the full directional wave spectrum. During the EU TULCS project, a full scale measurements campaign has been conducted onboard the CMA-CGM 13200 TEU container ship Rigoletto. She has been instrumented to measure deformation of the ship as well as the sea state encountered during its trip. This paper will focus on the sea state estimation. Three systems have been installed to estimate the sea state encountered by the Rigoletto: An X-band radar from Ocean Waves with WAMOS® system and two altimetric wave radars from RADAC®. Nevertheless, the measured significant wave height can be disturbed by several external elements like bow waves, sprays, sea surface ripples, etc… Furthermore, ship motions are also measured and can provide another estimation of the significant wave height using a specific algorithm developed by DCNS Research for the TULCS project. As all those estimations are inherently different, it is necessary to make a fusion of those data to provide a single estimation (“best estimate”) of the significant wave height. This paper will present the data fusion process developed for TULCS and show some first validation results.

scholarly journals A Simple Method for Retrieving Significant Wave Height from Dopplerized X-Band Radar

2016 ◽  
Author(s):  
Ruben Carrasco ◽  
Michael Streßer ◽  
Jochen Horstmann
Keyword(s):  
Wave Height ◽  
Significant Wave Height ◽  
Wave Spectrum ◽  
Doppler Velocity ◽  
Modulation Transfer ◽  
Simple Method ◽  
Backscatter Intensity ◽  
Significant Wave ◽  
X Band ◽  
Variance Spectrum

Abstract. Retrieving spectral wave parameters such as the peak wave direction and wave period from marine radar backscatter intensity is very well developed. However, the retrieval of significant wave height is difficult because the radar image spectrum (a backscatter intensity variance spectrum) has to be transferred to a wave spectrum (a surface elevation variance spectrum) using a modulation transfer function (MTF) which requires extensive calibration for each individual radar setup. In contrast to the backscatter intensity, the Doppler velocity measured by a coherent radar is induced by the radial velocity of the surface scattering and its periodic component is mainly the contribution of surface waves. Therefore, the variance of the Doppler velocity can be utilized to retrieve the significant wave height. Analysing approximately 100 days of Doppler velocity measurements of a coherent on receive radar operating at X-band with vertical polarization in transmit and receive, a simple relation was derived and validated to retrieve significant wave heights. Comparison to wave measurements of a wave rider buoy as well as an acoustic wave and current profiler resulted in a root mean square error of 0.24 m with a bias of 0.08 m. Furthermore, the different sources of error are discussed and investigated.

scholarly journals Features of X-Band Radar Backscattering Simulation Based on the Ocean Environmental Parameters in China Offshore Seas

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2450 ◽  
Author(s):  
Tao Wu ◽  
Zhensen Wu ◽  
Jiaji Wu ◽  
Gwanggil Jeon ◽  
Liwen Ma
Keyword(s):  
Wind Speed ◽  
Relative Error ◽  
Wave Spectrum ◽  
Environmental Parameters ◽  
Reanalysis Data ◽  
Practical Significance ◽  
Scale Model ◽  
Wind Speeds ◽  
Wave Parameters ◽  
X Band

The X-band marine radar has been employed as a remote sensing tool for sea state monitoring. However, there are few literatures about sea spectra considering both the wave parameters and short wind-wave spectra in China Offshore Seas, which are of theoretical and practical significance. Based on the wave parameters acquired from the European Centre for Medium-Range Weather Forecasts reanalysis data (ERA-Interim reanalysis data) during 36 months from 2015 to 2017, a finite depth sea spectrum considering both wind speeds and ocean environmental parameters is established in this study. The wave spectrum is then built into a modified two-scale model, which can be related to the ocean environmental parameters (wind speeds and wave parameters). The final results are the mean backscattering coefficients over the variety of sea states at a given wind speed. As the model predicts, the monthly maximum backscattering coefficients in different seas change slowly (within 4 dB). In addition, the differences of the backscattering coefficients in different seas are quite small during azimuthal angles of 0° to 90° and 270° to 360° with a relative error within 1.5 dB at low wind speed (5 m/s) and 2 dB at high wind speed (10 m/s). With the method in the paper, a corrected result from the experiment can be achieved based on the relative error analysis in different conditions.

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