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- W4386971141 abstract "Abstract Estimation of ocean wave conditions is extremely crucial for the planning and execution of demanding marine operations. Further, the Response Based Decision-Making requires accurate wave inputs to derive the responses using a numerical model. The X-band marine radars, installed on top of the vessels, are cost-effective means to assess the incoming wave field. Dedicated full-scale measurements were conducted using the research vessel Gunnerus in the Breisundet field, located on the west coast of Norway. After interaction with the ocean waves, the electromagnetic waves from the radar are backscattered based on the Bragg scattering mechanism. The radar digitizes the backscattered signal in the form of intensity images. 3-Dimensional (3-D) Fast Fourier Transform (FFT) was adopted to convert the temporal sequence of backscattered images to the wavenumber-frequency representations. The current velocity components estimated using the least-squares approach showed better agreement with the buoy-based current measurements. Then the wave-related components were extracted based on the linear wave dispersion relationship. Subsequently, the spectra were corrected for the shadowing effect using modulation transfer functions. Finally, the radar-based wave measurements were scaled using the nearby wave buoy records. The estimation of wave spectra improved considerably after the application of the Modulation Transfer Function (MTF). The spectra at the mid-range gave the best results when studying the effects due to range dependency. The spectra processed from radar images were validated using wave buoy measurements." @default.
- W4386971141 created "2023-09-23" @default.
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- W4386971141 date "2023-06-11" @default.
- W4386971141 modified "2023-09-29" @default.
- W4386971141 title "Retrieval of Ocean Wave Spectra From X-Band Marine Radar Images Using Inversion Schemes Based on Auto-Spectral Analysis" @default.
- W4386971141 doi "https://doi.org/10.1115/omae2023-104877" @default.
- W4386971141 hasPublicationYear "2023" @default.
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