A Directional Wave Spectrum Inversion Algorithm with HF Surface Wave Radar Network
In high-frequency surface wave radar (HFSWR) systems, the retrieval of the directional wave spectrum has remained challenging, especially in the case of echoes from long ranges with a low signal-to-noise ratio (SNR). Therefore, a quadratic programming algorithm based on the regularization technique...
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MDPI AG
2025-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/15/2573 |
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| author | Fuqi Mo Xiongbin Wu Xiaoyan Li Liang Yu Heng Zhou |
| author_facet | Fuqi Mo Xiongbin Wu Xiaoyan Li Liang Yu Heng Zhou |
| author_sort | Fuqi Mo |
| collection | DOAJ |
| description | In high-frequency surface wave radar (HFSWR) systems, the retrieval of the directional wave spectrum has remained challenging, especially in the case of echoes from long ranges with a low signal-to-noise ratio (SNR). Therefore, a quadratic programming algorithm based on the regularization technique is proposed with an empirical criterion for estimating the optimal regularization parameter, which minimizes the effect of noise to obtain more accurate inversion results. The reliability of the inversion method is preliminarily verified using simulated Doppler spectra under different wind speeds, wind directions, and SNRs. The directional wave spectra inverted from a radar network with two multiple-input multiple-output (MIMO) systems are basically consistent with those from the ERA5 data, while there is a limitation for the very concentrated directional distribution due to the truncated second order in the Fourier series. Further, in the field experiment during a storm that lasted three days, the wave parameters are calculated from the inverted directional spectra and compared with the ERA5 data. The results are shown to be in reasonable agreement at four typical locations in the core detection area. In addition, reasonable performance is also obtained under the condition of low SNRs, which further verifies the effectiveness of the proposed inversion algorithm. |
| format | Article |
| id | doaj-art-70cfbbe0636c4f03bb3d262b1d33bb66 |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-70cfbbe0636c4f03bb3d262b1d33bb662025-08-20T04:00:51ZengMDPI AGRemote Sensing2072-42922025-07-011715257310.3390/rs17152573A Directional Wave Spectrum Inversion Algorithm with HF Surface Wave Radar NetworkFuqi Mo0Xiongbin Wu1Xiaoyan Li2Liang Yu3Heng Zhou4School of Earth and Space Science and Technology, Wuhan University, Wuhan 430072, ChinaSchool of Earth and Space Science and Technology, Wuhan University, Wuhan 430072, ChinaSchool of Earth and Space Science and Technology, Wuhan University, Wuhan 430072, ChinaSchool of Earth and Space Science and Technology, Wuhan University, Wuhan 430072, ChinaSchool of Earth and Space Science and Technology, Wuhan University, Wuhan 430072, ChinaIn high-frequency surface wave radar (HFSWR) systems, the retrieval of the directional wave spectrum has remained challenging, especially in the case of echoes from long ranges with a low signal-to-noise ratio (SNR). Therefore, a quadratic programming algorithm based on the regularization technique is proposed with an empirical criterion for estimating the optimal regularization parameter, which minimizes the effect of noise to obtain more accurate inversion results. The reliability of the inversion method is preliminarily verified using simulated Doppler spectra under different wind speeds, wind directions, and SNRs. The directional wave spectra inverted from a radar network with two multiple-input multiple-output (MIMO) systems are basically consistent with those from the ERA5 data, while there is a limitation for the very concentrated directional distribution due to the truncated second order in the Fourier series. Further, in the field experiment during a storm that lasted three days, the wave parameters are calculated from the inverted directional spectra and compared with the ERA5 data. The results are shown to be in reasonable agreement at four typical locations in the core detection area. In addition, reasonable performance is also obtained under the condition of low SNRs, which further verifies the effectiveness of the proposed inversion algorithm.https://www.mdpi.com/2072-4292/17/15/2573HFSWRradar networkdirectional wave spectrumquadratic programmingregularization technique |
| spellingShingle | Fuqi Mo Xiongbin Wu Xiaoyan Li Liang Yu Heng Zhou A Directional Wave Spectrum Inversion Algorithm with HF Surface Wave Radar Network Remote Sensing HFSWR radar network directional wave spectrum quadratic programming regularization technique |
| title | A Directional Wave Spectrum Inversion Algorithm with HF Surface Wave Radar Network |
| title_full | A Directional Wave Spectrum Inversion Algorithm with HF Surface Wave Radar Network |
| title_fullStr | A Directional Wave Spectrum Inversion Algorithm with HF Surface Wave Radar Network |
| title_full_unstemmed | A Directional Wave Spectrum Inversion Algorithm with HF Surface Wave Radar Network |
| title_short | A Directional Wave Spectrum Inversion Algorithm with HF Surface Wave Radar Network |
| title_sort | directional wave spectrum inversion algorithm with hf surface wave radar network |
| topic | HFSWR radar network directional wave spectrum quadratic programming regularization technique |
| url | https://www.mdpi.com/2072-4292/17/15/2573 |
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