Absolute Calibration of Weather Radars Using Metal Spheres Based on Sector Scanning.
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| Title: | Absolute Calibration of Weather Radars Using Metal Spheres Based on Sector Scanning. |
|---|---|
| Authors: | Ye, Fei1 (AUTHOR), Wang, Xumin2 (AUTHOR), Li, Feifei3 (AUTHOR) lifeifei@cma.gov.cn, Yin, Jiazhi1 (AUTHOR), Cao, Jiaxuan1,2 (AUTHOR), Yang, Qian1,3 (AUTHOR), Huang, Zehao1 (AUTHOR), Li, Xuehua2 (AUTHOR) |
| Source: | Remote Sensing. Jun2026, Vol. 18 Issue 12, p1942. 20p. |
| Subjects: | Radar meteorology, Scanning systems, Spheres, Drone aircraft |
| Abstract: | Highlights: What are the main findings? Sector scanning significantly improves sampling coverage and data density compared with cross scanning. A three-dimensional ellipsoidal model effectively corrects range-bin crossing effects and enhances echo intensity and beamwidth retrieval accuracy. What are the implications of the main findings? The proposed method provides a more robust and accurate approach for weather radar metal sphere calibration under complex conditions. Combining cross scanning and sector scanning is recommended for efficient and high-precision operational calibration. To address the limitations of the traditional cross-scanning method in absolute calibration of weather radars using metal spheres, including insufficient spatial coverage, limited target acquisition efficiency, and echo underestimation in inter-range bins, this study proposes a sector scanning field calibration method. In this approach, standard metal spheres are suspended from UAVs, and a three-dimensional scanning volume around their theoretical positions is constructed to enable high-density echo sampling. By applying drive backlash correction, quadratic Gaussian surface fitting, and three-dimensional ellipsoid model inversion, key radar parameters can be retrieved. Experimental results show that the improved sector scanning method enhances automation, accuracy, and robustness in field environments and minor target drifts. The experiments were conducted under low-wind and low-clutter conditions. The average calibration error of antenna pointing is 0.08°, the average error of echo intensity calibration is 0.3 dB, the average beamwidth error is 0.07°, the range resolution is 6.6 m, and the average radial ranging error is 14 m. These results indicate that the proposed method can meet the main calibration requirements of weather radars in the present experiments. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 194915075 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Absolute Calibration of Weather Radars Using Metal Spheres Based on Sector Scanning. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ye%2C+Fei%22">Ye, Fei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Xumin%22">Wang, Xumin</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Feifei%22">Li, Feifei</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> lifeifei@cma.gov.cn</i><br /><searchLink fieldCode="AR" term="%22Yin%2C+Jiazhi%22">Yin, Jiazhi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cao%2C+Jiaxuan%22">Cao, Jiaxuan</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yang%2C+Qian%22">Yang, Qian</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Huang%2C+Zehao%22">Huang, Zehao</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Xuehua%22">Li, Xuehua</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Jun2026, Vol. 18 Issue 12, p1942. 20p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Radar+meteorology%22">Radar meteorology</searchLink><br /><searchLink fieldCode="DE" term="%22Scanning+systems%22">Scanning systems</searchLink><br /><searchLink fieldCode="DE" term="%22Spheres%22">Spheres</searchLink><br /><searchLink fieldCode="DE" term="%22Drone+aircraft%22">Drone aircraft</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Highlights: What are the main findings? Sector scanning significantly improves sampling coverage and data density compared with cross scanning. A three-dimensional ellipsoidal model effectively corrects range-bin crossing effects and enhances echo intensity and beamwidth retrieval accuracy. What are the implications of the main findings? The proposed method provides a more robust and accurate approach for weather radar metal sphere calibration under complex conditions. Combining cross scanning and sector scanning is recommended for efficient and high-precision operational calibration. To address the limitations of the traditional cross-scanning method in absolute calibration of weather radars using metal spheres, including insufficient spatial coverage, limited target acquisition efficiency, and echo underestimation in inter-range bins, this study proposes a sector scanning field calibration method. In this approach, standard metal spheres are suspended from UAVs, and a three-dimensional scanning volume around their theoretical positions is constructed to enable high-density echo sampling. By applying drive backlash correction, quadratic Gaussian surface fitting, and three-dimensional ellipsoid model inversion, key radar parameters can be retrieved. Experimental results show that the improved sector scanning method enhances automation, accuracy, and robustness in field environments and minor target drifts. The experiments were conducted under low-wind and low-clutter conditions. The average calibration error of antenna pointing is 0.08°, the average error of echo intensity calibration is 0.3 dB, the average beamwidth error is 0.07°, the range resolution is 6.6 m, and the average radial ranging error is 14 m. These results indicate that the proposed method can meet the main calibration requirements of weather radars in the present experiments. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs18121942 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 20 StartPage: 1942 Subjects: – SubjectFull: Radar meteorology Type: general – SubjectFull: Scanning systems Type: general – SubjectFull: Spheres Type: general – SubjectFull: Drone aircraft Type: general Titles: – TitleFull: Absolute Calibration of Weather Radars Using Metal Spheres Based on Sector Scanning. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ye, Fei – PersonEntity: Name: NameFull: Wang, Xumin – PersonEntity: Name: NameFull: Li, Feifei – PersonEntity: Name: NameFull: Yin, Jiazhi – PersonEntity: Name: NameFull: Cao, Jiaxuan – PersonEntity: Name: NameFull: Yang, Qian – PersonEntity: Name: NameFull: Huang, Zehao – PersonEntity: Name: NameFull: Li, Xuehua IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 18 – Type: issue Value: 12 Titles: – TitleFull: Remote Sensing Type: main |
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