Retrieval of Three-Dimensional Wave Surfaces from X-Band Marine Radar Images Utilizing Enhanced Pix2Pix Model
In this study, we propose a novel method for retrieving the three-dimensional (3D) wave surface from sea clutter using both simulated and measured data. First, the linear wave superposition model and modulation principle are employed to generate simulated datasets comprising 3D wave surfaces and cor...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/12/12/2229 |
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| _version_ | 1850049822753554432 |
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| author | Lingyi Hou Xiao Wang Bo Yang Zhiyuan Wei Yuwen Sun Yuxiang Ma |
| author_facet | Lingyi Hou Xiao Wang Bo Yang Zhiyuan Wei Yuwen Sun Yuxiang Ma |
| author_sort | Lingyi Hou |
| collection | DOAJ |
| description | In this study, we propose a novel method for retrieving the three-dimensional (3D) wave surface from sea clutter using both simulated and measured data. First, the linear wave superposition model and modulation principle are employed to generate simulated datasets comprising 3D wave surfaces and corresponding sea clutter. Subsequently, we develop a Pix2Pix model enhanced with a self-attention mechanism and a multiscale discriminator to effectively capture the nonlinear relationship between the simulated 3D wave surfaces and sea clutter. The model’s performance is evaluated through error analysis, comparisons of wave number spectra, and differences in wave surface reconstructions using a dedicated test set. Finally, the trained model is applied to reconstruct wave surfaces from sea clutter data collected aboard a ship, with results benchmarked against those derived from the Schrödinger equation. The findings demonstrate that the proposed model excels in preserving high-frequency image details while ensuring precise alignment between reconstructed images. Furthermore, it achieves superior retrieval accuracy compared to traditional approaches, highlighting its potential for advancing wave surface retrieval techniques. |
| format | Article |
| id | doaj-art-2c31ebfcd4904aad9017497ab54c2313 |
| institution | DOAJ |
| issn | 2077-1312 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-2c31ebfcd4904aad9017497ab54c23132025-08-20T02:53:38ZengMDPI AGJournal of Marine Science and Engineering2077-13122024-12-011212222910.3390/jmse12122229Retrieval of Three-Dimensional Wave Surfaces from X-Band Marine Radar Images Utilizing Enhanced Pix2Pix ModelLingyi Hou0Xiao Wang1Bo Yang2Zhiyuan Wei3Yuwen Sun4Yuxiang Ma5School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, ChinaDepartment of Navigation, PLA Dalian Naval Academy, Dalian 116018, ChinaDepartment of Navigation, PLA Dalian Naval Academy, Dalian 116018, ChinaDepartment of Navigation, PLA Dalian Naval Academy, Dalian 116018, ChinaSchool of Mechanical Engineering, Dalian University of Technology, Dalian 116024, ChinaState Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, ChinaIn this study, we propose a novel method for retrieving the three-dimensional (3D) wave surface from sea clutter using both simulated and measured data. First, the linear wave superposition model and modulation principle are employed to generate simulated datasets comprising 3D wave surfaces and corresponding sea clutter. Subsequently, we develop a Pix2Pix model enhanced with a self-attention mechanism and a multiscale discriminator to effectively capture the nonlinear relationship between the simulated 3D wave surfaces and sea clutter. The model’s performance is evaluated through error analysis, comparisons of wave number spectra, and differences in wave surface reconstructions using a dedicated test set. Finally, the trained model is applied to reconstruct wave surfaces from sea clutter data collected aboard a ship, with results benchmarked against those derived from the Schrödinger equation. The findings demonstrate that the proposed model excels in preserving high-frequency image details while ensuring precise alignment between reconstructed images. Furthermore, it achieves superior retrieval accuracy compared to traditional approaches, highlighting its potential for advancing wave surface retrieval techniques.https://www.mdpi.com/2077-1312/12/12/2229X-band marine radar3D wave surfacesea clutterPix2Pixself-attention |
| spellingShingle | Lingyi Hou Xiao Wang Bo Yang Zhiyuan Wei Yuwen Sun Yuxiang Ma Retrieval of Three-Dimensional Wave Surfaces from X-Band Marine Radar Images Utilizing Enhanced Pix2Pix Model Journal of Marine Science and Engineering X-band marine radar 3D wave surface sea clutter Pix2Pix self-attention |
| title | Retrieval of Three-Dimensional Wave Surfaces from X-Band Marine Radar Images Utilizing Enhanced Pix2Pix Model |
| title_full | Retrieval of Three-Dimensional Wave Surfaces from X-Band Marine Radar Images Utilizing Enhanced Pix2Pix Model |
| title_fullStr | Retrieval of Three-Dimensional Wave Surfaces from X-Band Marine Radar Images Utilizing Enhanced Pix2Pix Model |
| title_full_unstemmed | Retrieval of Three-Dimensional Wave Surfaces from X-Band Marine Radar Images Utilizing Enhanced Pix2Pix Model |
| title_short | Retrieval of Three-Dimensional Wave Surfaces from X-Band Marine Radar Images Utilizing Enhanced Pix2Pix Model |
| title_sort | retrieval of three dimensional wave surfaces from x band marine radar images utilizing enhanced pix2pix model |
| topic | X-band marine radar 3D wave surface sea clutter Pix2Pix self-attention |
| url | https://www.mdpi.com/2077-1312/12/12/2229 |
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