Improved Moments Estimation for Ground-Based K-Band Doppler Radar Using Cost Function Method
An improved moments estimation algorithm used in a newly developed K-band wind profiler to obtain accurate 3-D profiles of wind velocity along the altitude is described. The signal-to-noise ratio (SNR) of turbulent echoes detected by millimeter-wave radar is usually low, making it becomes a challeng...
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IEEE
2022-01-01
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Series: | IEEE Access |
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Online Access: | https://ieeexplore.ieee.org/document/9736160/ |
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author | Yirong Li Rui Wang Yong Luo Hua Li Guangli Yang |
author_facet | Yirong Li Rui Wang Yong Luo Hua Li Guangli Yang |
author_sort | Yirong Li |
collection | DOAJ |
description | An improved moments estimation algorithm used in a newly developed K-band wind profiler to obtain accurate 3-D profiles of wind velocity along the altitude is described. The signal-to-noise ratio (SNR) of turbulent echoes detected by millimeter-wave radar is usually low, making it becomes a challenging task to determine accurate Doppler profiles. And if wind profilers can provide quick estimates of wind, they will have greater applicability in automated, real-time environments. The improved method combines the concepts of adaptive Doppler windows and profile chain construction, reduces the search range of prospective spectral peaks by using adaptive Doppler windows, and designs new multiparameter cost functions to determine velocity profiles by studying the wind shear in the surface boundary layer. The algorithm can effectively identify the atmospheric echo components of each range bin even under the condition of low SNR, and the computational time is decreased by at least 18% compared with the previous algorithms. The proposed method is tested on the real wind radar datasets to verify its robustness and reliability. The wind information obtained by four different algorithms is compared with the data obtained from the meteorological mast of the Gaoyou wind farm in China. The comparison results indicate that the proposed method shows a nicer match with the data of the mast, and it derives the winds more accurately in the atmosphere of the surface boundary layer. |
first_indexed | 2024-12-13T00:49:20Z |
format | Article |
id | doaj.art-d0b9af304daa4687ad9f186816c10273 |
institution | Directory Open Access Journal |
issn | 2169-3536 |
language | English |
last_indexed | 2024-12-13T00:49:20Z |
publishDate | 2022-01-01 |
publisher | IEEE |
record_format | Article |
series | IEEE Access |
spelling | doaj.art-d0b9af304daa4687ad9f186816c102732022-12-22T00:04:58ZengIEEEIEEE Access2169-35362022-01-0110320493205910.1109/ACCESS.2022.31596909736160Improved Moments Estimation for Ground-Based K-Band Doppler Radar Using Cost Function MethodYirong Li0https://orcid.org/0000-0002-7410-1440Rui Wang1https://orcid.org/0000-0002-7974-9510Yong Luo2https://orcid.org/0000-0002-1263-8429Hua Li3https://orcid.org/0000-0002-1029-2778Guangli Yang4https://orcid.org/0000-0001-5841-9830Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, ChinaShanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, ChinaShanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, ChinaShanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, ChinaShanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, ChinaAn improved moments estimation algorithm used in a newly developed K-band wind profiler to obtain accurate 3-D profiles of wind velocity along the altitude is described. The signal-to-noise ratio (SNR) of turbulent echoes detected by millimeter-wave radar is usually low, making it becomes a challenging task to determine accurate Doppler profiles. And if wind profilers can provide quick estimates of wind, they will have greater applicability in automated, real-time environments. The improved method combines the concepts of adaptive Doppler windows and profile chain construction, reduces the search range of prospective spectral peaks by using adaptive Doppler windows, and designs new multiparameter cost functions to determine velocity profiles by studying the wind shear in the surface boundary layer. The algorithm can effectively identify the atmospheric echo components of each range bin even under the condition of low SNR, and the computational time is decreased by at least 18% compared with the previous algorithms. The proposed method is tested on the real wind radar datasets to verify its robustness and reliability. The wind information obtained by four different algorithms is compared with the data obtained from the meteorological mast of the Gaoyou wind farm in China. The comparison results indicate that the proposed method shows a nicer match with the data of the mast, and it derives the winds more accurately in the atmosphere of the surface boundary layer.https://ieeexplore.ieee.org/document/9736160/Moments estimationwind profilersurface boundary layeradaptive Doppler windowprofile chain building |
spellingShingle | Yirong Li Rui Wang Yong Luo Hua Li Guangli Yang Improved Moments Estimation for Ground-Based K-Band Doppler Radar Using Cost Function Method IEEE Access Moments estimation wind profiler surface boundary layer adaptive Doppler window profile chain building |
title | Improved Moments Estimation for Ground-Based K-Band Doppler Radar Using Cost Function Method |
title_full | Improved Moments Estimation for Ground-Based K-Band Doppler Radar Using Cost Function Method |
title_fullStr | Improved Moments Estimation for Ground-Based K-Band Doppler Radar Using Cost Function Method |
title_full_unstemmed | Improved Moments Estimation for Ground-Based K-Band Doppler Radar Using Cost Function Method |
title_short | Improved Moments Estimation for Ground-Based K-Band Doppler Radar Using Cost Function Method |
title_sort | improved moments estimation for ground based k band doppler radar using cost function method |
topic | Moments estimation wind profiler surface boundary layer adaptive Doppler window profile chain building |
url | https://ieeexplore.ieee.org/document/9736160/ |
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