Retrieving Multiaspect Point Clouds From a Multichannel K-Band SAR Drone
Satellite and airborne synthetic aperture radar (SAR) systems are frequently used for topographic mapping. However, their limited scene aspects lead to reduced angular coverage, making them less effective in environments with complex surface structures and tall objects. This limitation can be overco...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10848217/ |
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| author | Peter Brotzer Emiliano Casalini David Small Alexander Damm Elias Mendez Dominguez |
| author_facet | Peter Brotzer Emiliano Casalini David Small Alexander Damm Elias Mendez Dominguez |
| author_sort | Peter Brotzer |
| collection | DOAJ |
| description | Satellite and airborne synthetic aperture radar (SAR) systems are frequently used for topographic mapping. However, their limited scene aspects lead to reduced angular coverage, making them less effective in environments with complex surface structures and tall objects. This limitation can be overcome by drone-based SAR systems, which are becoming increasingly advanced, but their potential for three-dimensional (3-D) imaging remains largely unexplored. In this article, we utilize multiaspect SAR data acquired with a K-band drone system with 700 MHz bandwidth and investigate the potential 3-D point cloud retrievals in high resolution. Through a series of experiments with increasingly complex 3-D structures, we evaluate the accuracy of the derived point clouds. Independent references—based on light detection and ranging (LiDAR) and 3-D construction models—are used to validate our results. Our findings demonstrate that the drone SAR system can produce accurate and complete point clouds, with average Chamfer distances on the order of 1 m compared to reference data, highlighting the significance of multiple aspect acquisitions for 3-D mapping applications. |
| format | Article |
| id | doaj-art-ceef3006ea544759bf2e36d1e03fa710 |
| institution | Kabale University |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-ceef3006ea544759bf2e36d1e03fa7102025-02-12T00:00:53ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-01185033504510.1109/JSTARS.2025.353212610848217Retrieving Multiaspect Point Clouds From a Multichannel K-Band SAR DronePeter Brotzer0https://orcid.org/0009-0001-6960-4537Emiliano Casalini1https://orcid.org/0000-0002-5298-9119David Small2https://orcid.org/0000-0002-1440-364XAlexander Damm3https://orcid.org/0000-0001-8965-3427Elias Mendez Dominguez4https://orcid.org/0000-0002-1461-9424Remote Sensing Laboratories, Department of Geography, University of Zurich, Zurich, SwitzerlandRemote Sensing Laboratories, Department of Geography, University of Zurich, Zurich, SwitzerlandRemote Sensing Laboratories, Department of Geography, University of Zurich, Zurich, SwitzerlandRemote Sensing Laboratories, Department of Geography, University of Zurich, Zurich, SwitzerlandRemote Sensing Laboratories, Department of Geography, University of Zurich, Zurich, SwitzerlandSatellite and airborne synthetic aperture radar (SAR) systems are frequently used for topographic mapping. However, their limited scene aspects lead to reduced angular coverage, making them less effective in environments with complex surface structures and tall objects. This limitation can be overcome by drone-based SAR systems, which are becoming increasingly advanced, but their potential for three-dimensional (3-D) imaging remains largely unexplored. In this article, we utilize multiaspect SAR data acquired with a K-band drone system with 700 MHz bandwidth and investigate the potential 3-D point cloud retrievals in high resolution. Through a series of experiments with increasingly complex 3-D structures, we evaluate the accuracy of the derived point clouds. Independent references—based on light detection and ranging (LiDAR) and 3-D construction models—are used to validate our results. Our findings demonstrate that the drone SAR system can produce accurate and complete point clouds, with average Chamfer distances on the order of 1 m compared to reference data, highlighting the significance of multiple aspect acquisitions for 3-D mapping applications.https://ieeexplore.ieee.org/document/10848217/3-D mappingbuildingsfrequency-modulated continuous-wave (FMCW)tomographyuncrewed aerial vehicle (UAV)urban areas |
| spellingShingle | Peter Brotzer Emiliano Casalini David Small Alexander Damm Elias Mendez Dominguez Retrieving Multiaspect Point Clouds From a Multichannel K-Band SAR Drone IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 3-D mapping buildings frequency-modulated continuous-wave (FMCW) tomography uncrewed aerial vehicle (UAV) urban areas |
| title | Retrieving Multiaspect Point Clouds From a Multichannel K-Band SAR Drone |
| title_full | Retrieving Multiaspect Point Clouds From a Multichannel K-Band SAR Drone |
| title_fullStr | Retrieving Multiaspect Point Clouds From a Multichannel K-Band SAR Drone |
| title_full_unstemmed | Retrieving Multiaspect Point Clouds From a Multichannel K-Band SAR Drone |
| title_short | Retrieving Multiaspect Point Clouds From a Multichannel K-Band SAR Drone |
| title_sort | retrieving multiaspect point clouds from a multichannel k band sar drone |
| topic | 3-D mapping buildings frequency-modulated continuous-wave (FMCW) tomography uncrewed aerial vehicle (UAV) urban areas |
| url | https://ieeexplore.ieee.org/document/10848217/ |
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