High-Resolution ISAR Imaging With Sparse Aperture VFM Waveforms Under Low SNR Condition
In recent years, the compressed sensing theory has been widely used in sparse aperture radar imaging. The inverse synthetic aperture radar (ISAR) imaging based on the sparse aperture echo of V-style frequency modulation (V-FM) waveform, which can mitigate the ambiguity appeared in range and velocity...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8744198/ |
| _version_ | 1818642260197113856 |
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| author | Jiyuan Chen Letao Xu Xiaoyi Pan Pu Zheng Shunping Xiao |
| author_facet | Jiyuan Chen Letao Xu Xiaoyi Pan Pu Zheng Shunping Xiao |
| author_sort | Jiyuan Chen |
| collection | DOAJ |
| description | In recent years, the compressed sensing theory has been widely used in sparse aperture radar imaging. The inverse synthetic aperture radar (ISAR) imaging based on the sparse aperture echo of V-style frequency modulation (V-FM) waveform, which can mitigate the ambiguity appeared in range and velocity, has been proposed in this paper. After analyzing and interpreting the reason why the VFM signal pulse compression needs to use dual channels, we built the VFM waveform sparse echo model and analyze the causes of echo sparseness. A modified weighted compressive sensing (MWCS) algorithm is proposed to obtain high-resolution images under strong noise environment. The innovation of this paper lies in the new weighting method and the iterative reconstruction algorithm. The experimental results are shown to demonstrate the validity of the proposed method. |
| first_indexed | 2024-12-16T23:40:14Z |
| format | Article |
| id | doaj.art-097936e9f9174144a4af745bbc084543 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T23:40:14Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-097936e9f9174144a4af745bbc0845432022-12-21T22:11:37ZengIEEEIEEE Access2169-35362019-01-01711065111065910.1109/ACCESS.2019.29244938744198High-Resolution ISAR Imaging With Sparse Aperture VFM Waveforms Under Low SNR ConditionJiyuan Chen0https://orcid.org/0000-0003-4103-8294Letao Xu1Xiaoyi Pan2Pu Zheng3Shunping Xiao4State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, National University of Defense Technology, Changsha, ChinaAcademy of Naval Research, Beijing, ChinaState Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, National University of Defense Technology, Changsha, ChinaNational Key Laboratory of Science and Technology on Blind Signal Processing, Chengdu, ChinaState Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System, National University of Defense Technology, Changsha, ChinaIn recent years, the compressed sensing theory has been widely used in sparse aperture radar imaging. The inverse synthetic aperture radar (ISAR) imaging based on the sparse aperture echo of V-style frequency modulation (V-FM) waveform, which can mitigate the ambiguity appeared in range and velocity, has been proposed in this paper. After analyzing and interpreting the reason why the VFM signal pulse compression needs to use dual channels, we built the VFM waveform sparse echo model and analyze the causes of echo sparseness. A modified weighted compressive sensing (MWCS) algorithm is proposed to obtain high-resolution images under strong noise environment. The innovation of this paper lies in the new weighting method and the iterative reconstruction algorithm. The experimental results are shown to demonstrate the validity of the proposed method.https://ieeexplore.ieee.org/document/8744198/VFM waveformsparse signal modelISAR imaginglow SNR condition |
| spellingShingle | Jiyuan Chen Letao Xu Xiaoyi Pan Pu Zheng Shunping Xiao High-Resolution ISAR Imaging With Sparse Aperture VFM Waveforms Under Low SNR Condition IEEE Access VFM waveform sparse signal model ISAR imaging low SNR condition |
| title | High-Resolution ISAR Imaging With Sparse Aperture VFM Waveforms Under Low SNR Condition |
| title_full | High-Resolution ISAR Imaging With Sparse Aperture VFM Waveforms Under Low SNR Condition |
| title_fullStr | High-Resolution ISAR Imaging With Sparse Aperture VFM Waveforms Under Low SNR Condition |
| title_full_unstemmed | High-Resolution ISAR Imaging With Sparse Aperture VFM Waveforms Under Low SNR Condition |
| title_short | High-Resolution ISAR Imaging With Sparse Aperture VFM Waveforms Under Low SNR Condition |
| title_sort | high resolution isar imaging with sparse aperture vfm waveforms under low snr condition |
| topic | VFM waveform sparse signal model ISAR imaging low SNR condition |
| url | https://ieeexplore.ieee.org/document/8744198/ |
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