A Full-Polarization Radar Image Reconstruction Method with Orthogonal Coding Apertures
Imaging radar is widely applied in both military and civil fields, including remote sensing. In recent years, polarization information has attracted more and more attention in the imaging radar. The orthogonality between different channels is always the core problem for the full-polarization imaging...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/22/4626 |
| _version_ | 1797508617754116096 |
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| author | Tiehua Zhao Qihua Wu Feng Zhao Zhiming Xu Shunping Xiao |
| author_facet | Tiehua Zhao Qihua Wu Feng Zhao Zhiming Xu Shunping Xiao |
| author_sort | Tiehua Zhao |
| collection | DOAJ |
| description | Imaging radar is widely applied in both military and civil fields, including remote sensing. In recent years, polarization information has attracted more and more attention in the imaging radar. The orthogonality between different channels is always the core problem for the full-polarization imaging radar. To solve this problem, an image reconstruction method using orthogonal coding apertures technique is proposed for full-polarization imaging radar in this paper. Firstly, the signal model of the orthogonal coding apertures is proposed. This model realizes the ideal time-domain orthogonality between switching two channels by the apertures with two trains of orthogonal codes. Then, a multichannel joint reconstruction method based on compressed sensing is proposed for the imaging processing, which is named the coded aperture simultaneous orthogonal matching pursuit (CAS-OMP) algorithm. The proposed algorithm combines the information of all polarization channels so as to ensure the consistency of the scattering point position obtained by each polarization channel and also improves the reconstruction accuracy. Finally, the simulation experiments using both the simple scaled model of the satellite and measured data of an unmanned aerial vehicle (UAV) are conducted, and the effectiveness of the proposed method is verified. |
| first_indexed | 2024-03-10T05:06:27Z |
| format | Article |
| id | doaj.art-cc4091feba444df5b3534fc4be83521b |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T05:06:27Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-cc4091feba444df5b3534fc4be83521b2023-11-23T01:20:34ZengMDPI AGRemote Sensing2072-42922021-11-011322462610.3390/rs13224626A Full-Polarization Radar Image Reconstruction Method with Orthogonal Coding AperturesTiehua Zhao0Qihua Wu1Feng Zhao2Zhiming Xu3Shunping Xiao4State Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System, National University of Defense Technology, Changsha 410005, ChinaState Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System, National University of Defense Technology, Changsha 410005, ChinaState Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System, National University of Defense Technology, Changsha 410005, ChinaState Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System, National University of Defense Technology, Changsha 410005, ChinaState Key Laboratory of Complex Electromagnetic Environmental Effects on Electronics and Information System, National University of Defense Technology, Changsha 410005, ChinaImaging radar is widely applied in both military and civil fields, including remote sensing. In recent years, polarization information has attracted more and more attention in the imaging radar. The orthogonality between different channels is always the core problem for the full-polarization imaging radar. To solve this problem, an image reconstruction method using orthogonal coding apertures technique is proposed for full-polarization imaging radar in this paper. Firstly, the signal model of the orthogonal coding apertures is proposed. This model realizes the ideal time-domain orthogonality between switching two channels by the apertures with two trains of orthogonal codes. Then, a multichannel joint reconstruction method based on compressed sensing is proposed for the imaging processing, which is named the coded aperture simultaneous orthogonal matching pursuit (CAS-OMP) algorithm. The proposed algorithm combines the information of all polarization channels so as to ensure the consistency of the scattering point position obtained by each polarization channel and also improves the reconstruction accuracy. Finally, the simulation experiments using both the simple scaled model of the satellite and measured data of an unmanned aerial vehicle (UAV) are conducted, and the effectiveness of the proposed method is verified.https://www.mdpi.com/2072-4292/13/22/4626compressed sensingjoint reconstructionorthogonal coding aperturepolarization radar imaging |
| spellingShingle | Tiehua Zhao Qihua Wu Feng Zhao Zhiming Xu Shunping Xiao A Full-Polarization Radar Image Reconstruction Method with Orthogonal Coding Apertures Remote Sensing compressed sensing joint reconstruction orthogonal coding aperture polarization radar imaging |
| title | A Full-Polarization Radar Image Reconstruction Method with Orthogonal Coding Apertures |
| title_full | A Full-Polarization Radar Image Reconstruction Method with Orthogonal Coding Apertures |
| title_fullStr | A Full-Polarization Radar Image Reconstruction Method with Orthogonal Coding Apertures |
| title_full_unstemmed | A Full-Polarization Radar Image Reconstruction Method with Orthogonal Coding Apertures |
| title_short | A Full-Polarization Radar Image Reconstruction Method with Orthogonal Coding Apertures |
| title_sort | full polarization radar image reconstruction method with orthogonal coding apertures |
| topic | compressed sensing joint reconstruction orthogonal coding aperture polarization radar imaging |
| url | https://www.mdpi.com/2072-4292/13/22/4626 |
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