Elevation Spatial Variation Analysis and Compensation in GEO SAR Imaging
Due to geosynchronous synthetic aperture radar’s (GEO SAR) high orbit and low relative speed, the integration time reaches up to hundreds of seconds for a fine resolution. The short revisit cycle is essential for remote sensing applications such as disaster monitoring and vegetation measurements. Th...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/10/1888 |
| _version_ | 1797534477822459904 |
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| author | Faguang Chang Dexin Li Zhen Dong Yang Huang Zhihua He Xing Chen |
| author_facet | Faguang Chang Dexin Li Zhen Dong Yang Huang Zhihua He Xing Chen |
| author_sort | Faguang Chang |
| collection | DOAJ |
| description | Due to geosynchronous synthetic aperture radar’s (GEO SAR) high orbit and low relative speed, the integration time reaches up to hundreds of seconds for a fine resolution. The short revisit cycle is essential for remote sensing applications such as disaster monitoring and vegetation measurements. Three-dimensional (3D) scene imaging mode is crucial for long-term observation using GEO SAR. However, this mode will bring a new kind of space-variant error in elevation. In this paper, we focus on the analysis of the elevation space-variant error. First, the decorrelation problems caused by the spatial variation are presented. Second, by combining with the SAR imaging geometry, the elevation spatial variation is decomposed into two-dimensional (2D) space variation of range and azimuth. Third, an imaging algorithm is proposed to solve the 3D space variation and improve the focusing depth. Finally, simulations with dot-matrix targets and distributed targets are performed to validate the imaging method. |
| first_indexed | 2024-03-10T11:30:07Z |
| format | Article |
| id | doaj.art-cffe5aaf19314c3d80241ba78683b641 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T11:30:07Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-cffe5aaf19314c3d80241ba78683b6412023-11-21T19:19:02ZengMDPI AGRemote Sensing2072-42922021-05-011310188810.3390/rs13101888Elevation Spatial Variation Analysis and Compensation in GEO SAR ImagingFaguang Chang0Dexin Li1Zhen Dong2Yang Huang3Zhihua He4Xing Chen5College of Electronic Science and Technology, National University of Defense Technology, No. 109 Deya Road, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, No. 109 Deya Road, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, No. 109 Deya Road, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, No. 109 Deya Road, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, No. 109 Deya Road, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, No. 109 Deya Road, Changsha 410073, ChinaDue to geosynchronous synthetic aperture radar’s (GEO SAR) high orbit and low relative speed, the integration time reaches up to hundreds of seconds for a fine resolution. The short revisit cycle is essential for remote sensing applications such as disaster monitoring and vegetation measurements. Three-dimensional (3D) scene imaging mode is crucial for long-term observation using GEO SAR. However, this mode will bring a new kind of space-variant error in elevation. In this paper, we focus on the analysis of the elevation space-variant error. First, the decorrelation problems caused by the spatial variation are presented. Second, by combining with the SAR imaging geometry, the elevation spatial variation is decomposed into two-dimensional (2D) space variation of range and azimuth. Third, an imaging algorithm is proposed to solve the 3D space variation and improve the focusing depth. Finally, simulations with dot-matrix targets and distributed targets are performed to validate the imaging method.https://www.mdpi.com/2072-4292/13/10/1888geosynchronous synthetic aperture radar (GEO SAR)three-dimensional (3D) scene imagingelevation spatial variation errordepth of focus |
| spellingShingle | Faguang Chang Dexin Li Zhen Dong Yang Huang Zhihua He Xing Chen Elevation Spatial Variation Analysis and Compensation in GEO SAR Imaging Remote Sensing geosynchronous synthetic aperture radar (GEO SAR) three-dimensional (3D) scene imaging elevation spatial variation error depth of focus |
| title | Elevation Spatial Variation Analysis and Compensation in GEO SAR Imaging |
| title_full | Elevation Spatial Variation Analysis and Compensation in GEO SAR Imaging |
| title_fullStr | Elevation Spatial Variation Analysis and Compensation in GEO SAR Imaging |
| title_full_unstemmed | Elevation Spatial Variation Analysis and Compensation in GEO SAR Imaging |
| title_short | Elevation Spatial Variation Analysis and Compensation in GEO SAR Imaging |
| title_sort | elevation spatial variation analysis and compensation in geo sar imaging |
| topic | geosynchronous synthetic aperture radar (GEO SAR) three-dimensional (3D) scene imaging elevation spatial variation error depth of focus |
| url | https://www.mdpi.com/2072-4292/13/10/1888 |
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