scholarly journals Ocean Waves in K-distributed Clutter

2021 ◽  
Author(s):  
Stephen Bocquet
Keyword(s):  
Wave Spectrum ◽  
Grazing Angle ◽  
Ocean Waves ◽  
Distribution Model ◽  
Doppler Spectrum ◽  
Sea Clutter ◽  
Compound K ◽  
Ocean Wave Spectrum ◽  
Pulse Doppler ◽  
Coherent Radar

<div> <div> <div> <p>Two examples of low grazing angle radar sea clutter, both well described by the compound K-distribution model, are studied. Pulse Doppler processing is applied to obtain two dimensional range-time textures for the intensity, centroid and width of the Doppler spectrum. The first example exhibits a monochromatic swell pattern, allowing phase averaging to be applied to the textures. The second example has a more typical ocean wave spectrum. The intensity textures are gamma distributed, consistent with the compound K-distribution model, but the Doppler spectrum centroid and width textures are also found to be gamma distributed. Based on this analysis, a new method for simulation of coherent radar sea clutter is proposed, where separate memoryless nonlinear transformations are applied to a simulated water surface to generate the spatially and temporally varying intensity, centroid and width of the Doppler spectrum. The method builds on the evolving Doppler spectrum model for radar sea clutter simulation and established methods for simulation of water surfaces. </p> </div> </div> </div>

scholarly journals Ocean Waves in K-distributed Clutter

2021 ◽  
Author(s):  
Stephen Bocquet
Keyword(s):  
Wave Spectrum ◽  
Grazing Angle ◽  
Ocean Waves ◽  
Distribution Model ◽  
Doppler Spectrum ◽  
Sea Clutter ◽  
Compound K ◽  
Ocean Wave Spectrum ◽  
Pulse Doppler ◽  
Coherent Radar

<div> <div> <div> <p>Two examples of low grazing angle radar sea clutter, both well described by the compound K-distribution model, are studied. Pulse Doppler processing is applied to obtain two dimensional range-time textures for the intensity, centroid and width of the Doppler spectrum. The first example exhibits a monochromatic swell pattern, allowing phase averaging to be applied to the textures. The second example has a more typical ocean wave spectrum. The intensity textures are gamma distributed, consistent with the compound K-distribution model, but the Doppler spectrum centroid and width textures are also found to be gamma distributed. Based on this analysis, a new method for simulation of coherent radar sea clutter is proposed, where separate memoryless nonlinear transformations are applied to a simulated water surface to generate the spatially and temporally varying intensity, centroid and width of the Doppler spectrum. The method builds on the evolving Doppler spectrum model for radar sea clutter simulation and established methods for simulation of water surfaces. </p> </div> </div> </div>

Effects of Ocean Wave Spectrum Truncation on Sea Clutter Distribution in Numerical Simulations

2021 ◽  
Author(s):  
Yanlei Du ◽  
Jian Yang ◽  
Tao Liu ◽  
Liang Zeng ◽  
Tao Zhang ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Wave Spectrum ◽  
Ocean Wave ◽  
Sea Clutter ◽  
Ocean Wave Spectrum

scholarly journals The Wave Heights Distribution of Random Wave Based on Ocean Basin

Kapal ◽  
2020 ◽  
Vol 17 (3) ◽  
pp. 114-122
Author(s):  
Nurman Firdaus ◽  
Baharuddin Ali ◽  
Mochammad Nasir ◽  
M Muryadin
Keyword(s):  
Wave Height ◽  
Wave Spectrum ◽  
Ocean Waves ◽  
Ocean Basin ◽  
Distribution Model ◽  
Exceedance Probability ◽  
Random Wave ◽  
Theoretical Spectrum ◽  
Sea State ◽  
Wave Heights

The wave height parameter in ocean waves is one of the important information for a marine structure design. The present paper investigates the results of wave heights distribution from laboratory-generated for single sea state. Data of the random wave time series collected at the ocean basin are analyzed using the wave spectrum and compared with the theoretical spectrum in this study. The random wave data is varied with four sea states consisting of sea states 3, 4, 5 and 6 obtained from laboratory measurements. The parameter conditions of generated sea waves are represented by a value of significant wave height and wave peak period in the range of sea states. The individual wave heights data in each sea state are presented in the form of exceedance probability distribution and the predictions using a linear model. This study aims to estimate the wave heights distribution using the Rayleigh and Weibull distribution model. Furthermore, the accuracy of the wave heights distribution data's prediction results in each sea state has been compared and examined for both models. The applied linear models indicate similar and reasonable estimations on the observed data trends.

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.

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