Multiangle SAR Dataset Construction of Aircraft Targets Based on Angle Interpolation Simulation
With the expansion of Synthetic Aperture Radar (SAR) applications and the development of SAR data acquisition technology, multiangle SAR datasets of various typical targets need to be constructed. Presently, a comprehensive multiangle SAR image dataset for aircraft targets is still lacking. This stu...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
China Science Publishing & Media Ltd. (CSPM)
2022-08-01
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| Series: | Leida xuebao |
| Subjects: | |
| Online Access: | https://radars.ac.cn/cn/article/doi/10.12000/JR21193 |
| _version_ | 1797422461360275456 |
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| author | Ruyi WANG Hanqing ZHANG Bing HAN Yueting ZHANG Jiayi GUO Wen HONG Wei SUN Wenlong HU |
| author_facet | Ruyi WANG Hanqing ZHANG Bing HAN Yueting ZHANG Jiayi GUO Wen HONG Wei SUN Wenlong HU |
| author_sort | Ruyi WANG |
| collection | DOAJ |
| description | With the expansion of Synthetic Aperture Radar (SAR) applications and the development of SAR data acquisition technology, multiangle SAR datasets of various typical targets need to be constructed. Presently, a comprehensive multiangle SAR image dataset for aircraft targets is still lacking. This study explores a method of dataset construction based on the acquisition of actual data and intelligent simulation. Multiangle SAR images of aircraft targets are collected through flight tests, and the interpolation simulations of SAR images of specific angles are realized based on scattering analysis and self-attention generative adversarial network, which provide a new solution for dataset construction and expansion. Finally, under the assumption that some data are missing, the similarities between the simulated and actual images are evaluated using six evaluation indices, which verify the effectiveness of the proposed method. |
| first_indexed | 2024-03-09T07:32:38Z |
| format | Article |
| id | doaj.art-c5a9c8289163455589423328bdf82b14 |
| institution | Directory Open Access Journal |
| issn | 2095-283X |
| language | English |
| last_indexed | 2024-03-09T07:32:38Z |
| publishDate | 2022-08-01 |
| publisher | China Science Publishing & Media Ltd. (CSPM) |
| record_format | Article |
| series | Leida xuebao |
| spelling | doaj.art-c5a9c8289163455589423328bdf82b142023-12-03T05:47:06ZengChina Science Publishing & Media Ltd. (CSPM)Leida xuebao2095-283X2022-08-0111463765110.12000/JR21193R21193Multiangle SAR Dataset Construction of Aircraft Targets Based on Angle Interpolation SimulationRuyi WANG0Hanqing ZHANG1Bing HAN2Yueting ZHANG3Jiayi GUO4Wen HONG5Wei SUN6Wenlong HU7Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, ChinaWith the expansion of Synthetic Aperture Radar (SAR) applications and the development of SAR data acquisition technology, multiangle SAR datasets of various typical targets need to be constructed. Presently, a comprehensive multiangle SAR image dataset for aircraft targets is still lacking. This study explores a method of dataset construction based on the acquisition of actual data and intelligent simulation. Multiangle SAR images of aircraft targets are collected through flight tests, and the interpolation simulations of SAR images of specific angles are realized based on scattering analysis and self-attention generative adversarial network, which provide a new solution for dataset construction and expansion. Finally, under the assumption that some data are missing, the similarities between the simulated and actual images are evaluated using six evaluation indices, which verify the effectiveness of the proposed method.https://radars.ac.cn/cn/article/doi/10.12000/JR21193dataset constructionairplane objectimage simulationgenerative adversarial networkself-attention |
| spellingShingle | Ruyi WANG Hanqing ZHANG Bing HAN Yueting ZHANG Jiayi GUO Wen HONG Wei SUN Wenlong HU Multiangle SAR Dataset Construction of Aircraft Targets Based on Angle Interpolation Simulation Leida xuebao dataset construction airplane object image simulation generative adversarial network self-attention |
| title | Multiangle SAR Dataset Construction of Aircraft Targets Based on Angle Interpolation Simulation |
| title_full | Multiangle SAR Dataset Construction of Aircraft Targets Based on Angle Interpolation Simulation |
| title_fullStr | Multiangle SAR Dataset Construction of Aircraft Targets Based on Angle Interpolation Simulation |
| title_full_unstemmed | Multiangle SAR Dataset Construction of Aircraft Targets Based on Angle Interpolation Simulation |
| title_short | Multiangle SAR Dataset Construction of Aircraft Targets Based on Angle Interpolation Simulation |
| title_sort | multiangle sar dataset construction of aircraft targets based on angle interpolation simulation |
| topic | dataset construction airplane object image simulation generative adversarial network self-attention |
| url | https://radars.ac.cn/cn/article/doi/10.12000/JR21193 |
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