An Improved Multi-Threshold Clutter Filtering Algorithm for W-Band Cloud Radar Based on K-Means Clustering
This study investigates the application of an improved multi-threshold method based on the K-means algorithm for clutter filtering in W-band cloud and fog radar observations. Utilizing W-band millimeter-wave cloud and fog radar data collected from March to July 2023 in the Qingdao area, a dataset of...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/16/24/4640 |
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| author | Zhao Shi Lingjiang Huang Fengyuan Wu Yong Lei Huiying Wang Zhiya Tang |
| author_facet | Zhao Shi Lingjiang Huang Fengyuan Wu Yong Lei Huiying Wang Zhiya Tang |
| author_sort | Zhao Shi |
| collection | DOAJ |
| description | This study investigates the application of an improved multi-threshold method based on the K-means algorithm for clutter filtering in W-band cloud and fog radar observations. Utilizing W-band millimeter-wave cloud and fog radar data collected from March to July 2023 in the Qingdao area, a dataset of cloud and fog echo of different types was constructed and statistically analyzed. Subsequently, a multi-threshold clutter filtering method was proposed to identify and eliminate abnormal interferences such as noise spikes, radial interference, and suspended matter clutter. This method employs the basic data and spatiotemporal information from the cloud radar as feature variables for K-means clustering and dynamically adjusts thresholds based on the clustering results. The clutter-filtered data were further used for the verification analysis of cloud and fog identification. The results demonstrate that the proposed multi-threshold method effectively removes clutter and significantly reduces its impact on cloud and fog echo under weather conditions of clouds, fog, and coexisting cloud–fog, while controlling the loss of cloud and fog echo within the required accuracy range. |
| format | Article |
| id | doaj-art-a2745b96b5304c5b902021c2e7dfe977 |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-a2745b96b5304c5b902021c2e7dfe9772025-08-20T02:43:43ZengMDPI AGRemote Sensing2072-42922024-12-011624464010.3390/rs16244640An Improved Multi-Threshold Clutter Filtering Algorithm for W-Band Cloud Radar Based on K-Means ClusteringZhao Shi0Lingjiang Huang1Fengyuan Wu2Yong Lei3Huiying Wang4Zhiya Tang5College of Atmospheric Sounding, Chengdu University of Information Technology, Chengdu 610225, ChinaCollege of Atmospheric Sounding, Chengdu University of Information Technology, Chengdu 610225, ChinaCollege of Atmospheric Sounding, Chengdu University of Information Technology, Chengdu 610225, ChinaMeteorological Observation Center of CMA, Beijing 100081, ChinaNational Meteorological Information Center of CMA, Beijing 100081, ChinaCollege of Atmospheric Sounding, Chengdu University of Information Technology, Chengdu 610225, ChinaThis study investigates the application of an improved multi-threshold method based on the K-means algorithm for clutter filtering in W-band cloud and fog radar observations. Utilizing W-band millimeter-wave cloud and fog radar data collected from March to July 2023 in the Qingdao area, a dataset of cloud and fog echo of different types was constructed and statistically analyzed. Subsequently, a multi-threshold clutter filtering method was proposed to identify and eliminate abnormal interferences such as noise spikes, radial interference, and suspended matter clutter. This method employs the basic data and spatiotemporal information from the cloud radar as feature variables for K-means clustering and dynamically adjusts thresholds based on the clustering results. The clutter-filtered data were further used for the verification analysis of cloud and fog identification. The results demonstrate that the proposed multi-threshold method effectively removes clutter and significantly reduces its impact on cloud and fog echo under weather conditions of clouds, fog, and coexisting cloud–fog, while controlling the loss of cloud and fog echo within the required accuracy range.https://www.mdpi.com/2072-4292/16/24/4640W-band cloud radarclutter filteringK-meanscloud and fog identification |
| spellingShingle | Zhao Shi Lingjiang Huang Fengyuan Wu Yong Lei Huiying Wang Zhiya Tang An Improved Multi-Threshold Clutter Filtering Algorithm for W-Band Cloud Radar Based on K-Means Clustering Remote Sensing W-band cloud radar clutter filtering K-means cloud and fog identification |
| title | An Improved Multi-Threshold Clutter Filtering Algorithm for W-Band Cloud Radar Based on K-Means Clustering |
| title_full | An Improved Multi-Threshold Clutter Filtering Algorithm for W-Band Cloud Radar Based on K-Means Clustering |
| title_fullStr | An Improved Multi-Threshold Clutter Filtering Algorithm for W-Band Cloud Radar Based on K-Means Clustering |
| title_full_unstemmed | An Improved Multi-Threshold Clutter Filtering Algorithm for W-Band Cloud Radar Based on K-Means Clustering |
| title_short | An Improved Multi-Threshold Clutter Filtering Algorithm for W-Band Cloud Radar Based on K-Means Clustering |
| title_sort | improved multi threshold clutter filtering algorithm for w band cloud radar based on k means clustering |
| topic | W-band cloud radar clutter filtering K-means cloud and fog identification |
| url | https://www.mdpi.com/2072-4292/16/24/4640 |
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