Deterministic Sea Wave Reconstruction and Prediction Based on Coherent S-Band Radar Using Condition Number Regularized Least Squares
Coherent S-band radar is a remote sensing observation device with high spatial-temporal resolution and can be used to achieve deterministic sea wave reconstruction and prediction (DSWRP) technology. However, coherent S-band radar can observe nonlinear details of the sea surface due to its high resol...
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MDPI AG
2024-11-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/16/22/4147 |
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| author | Zhongqian Hu Zezong Chen Chen Zhao Xi Chen |
| author_facet | Zhongqian Hu Zezong Chen Chen Zhao Xi Chen |
| author_sort | Zhongqian Hu |
| collection | DOAJ |
| description | Coherent S-band radar is a remote sensing observation device with high spatial-temporal resolution and can be used to achieve deterministic sea wave reconstruction and prediction (DSWRP) technology. However, coherent S-band radar can observe nonlinear details of the sea surface due to its high resolution, which makes the propagation operator matrix an ill-conditioned overdetermined matrix. To solve this problem, this paper proposes a DSWRP scheme using condition number regularized least squares (CN-RLS) for coherent S-band radar. First, the space-time velocity information was obtained from the radar echo. Second, the CN-RLS method solved the phase-resolved model coefficients. Finally, the deterministic wave field was predicted according to the solved model coefficients. The proposed scheme was verified by simulation data and the real radar dataset observed by the coherent S-band wave-measuring radar onboard the ship XIANGYANGHONG-18 in the East China Sea in April 2024. The predicted wave elevation of the proposed method was compared with the wave elevation observed based on the X-band wave-measuring radar, and the root mean square error (RMSE) and correlation coefficient (CC) were 0.22 m and 0.76, respectively, which show that the proposed method could effectively implement the DSWRP technology. |
| format | Article |
| id | doaj-art-908d7d7c0b25444e96bef0db7ce1bb3f |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj-art-908d7d7c0b25444e96bef0db7ce1bb3f2025-08-20T01:54:08ZengMDPI AGRemote Sensing2072-42922024-11-011622414710.3390/rs16224147Deterministic Sea Wave Reconstruction and Prediction Based on Coherent S-Band Radar Using Condition Number Regularized Least SquaresZhongqian Hu0Zezong Chen1Chen Zhao2Xi Chen3School of Electronic Information, Wuhan University, Wuhan 430072, ChinaSchool of Electronic Information, Wuhan University, Wuhan 430072, ChinaSchool of Electronic Information, Wuhan University, Wuhan 430072, ChinaChina Ship Development and Design Center, Wuhan 430072, ChinaCoherent S-band radar is a remote sensing observation device with high spatial-temporal resolution and can be used to achieve deterministic sea wave reconstruction and prediction (DSWRP) technology. However, coherent S-band radar can observe nonlinear details of the sea surface due to its high resolution, which makes the propagation operator matrix an ill-conditioned overdetermined matrix. To solve this problem, this paper proposes a DSWRP scheme using condition number regularized least squares (CN-RLS) for coherent S-band radar. First, the space-time velocity information was obtained from the radar echo. Second, the CN-RLS method solved the phase-resolved model coefficients. Finally, the deterministic wave field was predicted according to the solved model coefficients. The proposed scheme was verified by simulation data and the real radar dataset observed by the coherent S-band wave-measuring radar onboard the ship XIANGYANGHONG-18 in the East China Sea in April 2024. The predicted wave elevation of the proposed method was compared with the wave elevation observed based on the X-band wave-measuring radar, and the root mean square error (RMSE) and correlation coefficient (CC) were 0.22 m and 0.76, respectively, which show that the proposed method could effectively implement the DSWRP technology.https://www.mdpi.com/2072-4292/16/22/4147remote sensingDSWRPnonlinear detailsCN-RLSmodel coefficients |
| spellingShingle | Zhongqian Hu Zezong Chen Chen Zhao Xi Chen Deterministic Sea Wave Reconstruction and Prediction Based on Coherent S-Band Radar Using Condition Number Regularized Least Squares Remote Sensing remote sensing DSWRP nonlinear details CN-RLS model coefficients |
| title | Deterministic Sea Wave Reconstruction and Prediction Based on Coherent S-Band Radar Using Condition Number Regularized Least Squares |
| title_full | Deterministic Sea Wave Reconstruction and Prediction Based on Coherent S-Band Radar Using Condition Number Regularized Least Squares |
| title_fullStr | Deterministic Sea Wave Reconstruction and Prediction Based on Coherent S-Band Radar Using Condition Number Regularized Least Squares |
| title_full_unstemmed | Deterministic Sea Wave Reconstruction and Prediction Based on Coherent S-Band Radar Using Condition Number Regularized Least Squares |
| title_short | Deterministic Sea Wave Reconstruction and Prediction Based on Coherent S-Band Radar Using Condition Number Regularized Least Squares |
| title_sort | deterministic sea wave reconstruction and prediction based on coherent s band radar using condition number regularized least squares |
| topic | remote sensing DSWRP nonlinear details CN-RLS model coefficients |
| url | https://www.mdpi.com/2072-4292/16/22/4147 |
| work_keys_str_mv | AT zhongqianhu deterministicseawavereconstructionandpredictionbasedoncoherentsbandradarusingconditionnumberregularizedleastsquares AT zezongchen deterministicseawavereconstructionandpredictionbasedoncoherentsbandradarusingconditionnumberregularizedleastsquares AT chenzhao deterministicseawavereconstructionandpredictionbasedoncoherentsbandradarusingconditionnumberregularizedleastsquares AT xichen deterministicseawavereconstructionandpredictionbasedoncoherentsbandradarusingconditionnumberregularizedleastsquares |