Moving target inverse synthetic aperture radar image resolution enhancement based on two‐dimensional block sparse signal reconstruction
Abstract To achieve the high‐resolution inverse synthetic aperture radar (ISAR) imaging of moving targets, the range Doppler method and compressed sensing technique can be used. However, those methods are generally faced with the problem of migration through range cells and basis mismatch problems,...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-11-01
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| Series: | IET Image Processing |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/ipr2.12310 |
| _version_ | 1797901424269459456 |
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| author | Xingyu He Ningning Tong Tao Liu |
| author_facet | Xingyu He Ningning Tong Tao Liu |
| author_sort | Xingyu He |
| collection | DOAJ |
| description | Abstract To achieve the high‐resolution inverse synthetic aperture radar (ISAR) imaging of moving targets, the range Doppler method and compressed sensing technique can be used. However, those methods are generally faced with the problem of migration through range cells and basis mismatch problems, and the imaging results can be improved. To solve these problems and improve the image quality, the problem of ISAR imaging is termed as a block‐sparse signal recovery problem by utilizing the block‐sparse structure of the ISAR images. A localized low‐rank promoting (LLP) method is introduced and extended to the complex case for the recovery of range compressed block‐sparse signals. The sparse recovery problem is solved by minimizing another function, which is the surrogate function that can be solved more effectively. Based on the LLP method, the coefficients of the range compressed echo signal are reconstructed and some 2 × 2 matrices can be obtained. And then the log‐determinant function is introduced to find the low rankness solutions for these matrices. Then the LLP method is also used in the cross‐range domain to reconstruct the ISAR image. Experimental results show that the proposed method can recover better focused and higher quality ISAR images compared with the traditional methods. |
| first_indexed | 2024-04-10T09:01:50Z |
| format | Article |
| id | doaj.art-12d00b462ca7434180d4b5fb88f5855c |
| institution | Directory Open Access Journal |
| issn | 1751-9659 1751-9667 |
| language | English |
| last_indexed | 2024-04-10T09:01:50Z |
| publishDate | 2021-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Image Processing |
| spelling | doaj.art-12d00b462ca7434180d4b5fb88f5855c2023-02-21T11:57:05ZengWileyIET Image Processing1751-96591751-96672021-11-0115133153315910.1049/ipr2.12310Moving target inverse synthetic aperture radar image resolution enhancement based on two‐dimensional block sparse signal reconstructionXingyu He0Ningning Tong1Tao Liu2Air Traffic Control and Navigation College Air Force Engineering University Xi'an Shaanxi People's Republic of ChinaAir and Missile Defense College Air Force Engineering University Xi'an Shaanxi People's Republic of ChinaTeaching and Research Guarantee Center Air Force Engineering University Xi'an Shaanxi People's Republic of ChinaAbstract To achieve the high‐resolution inverse synthetic aperture radar (ISAR) imaging of moving targets, the range Doppler method and compressed sensing technique can be used. However, those methods are generally faced with the problem of migration through range cells and basis mismatch problems, and the imaging results can be improved. To solve these problems and improve the image quality, the problem of ISAR imaging is termed as a block‐sparse signal recovery problem by utilizing the block‐sparse structure of the ISAR images. A localized low‐rank promoting (LLP) method is introduced and extended to the complex case for the recovery of range compressed block‐sparse signals. The sparse recovery problem is solved by minimizing another function, which is the surrogate function that can be solved more effectively. Based on the LLP method, the coefficients of the range compressed echo signal are reconstructed and some 2 × 2 matrices can be obtained. And then the log‐determinant function is introduced to find the low rankness solutions for these matrices. Then the LLP method is also used in the cross‐range domain to reconstruct the ISAR image. Experimental results show that the proposed method can recover better focused and higher quality ISAR images compared with the traditional methods.https://doi.org/10.1049/ipr2.12310Image and video codingRadar equipment, systems and applicationsOptimisation techniquesInterpolation and function approximation (numerical analysis) |
| spellingShingle | Xingyu He Ningning Tong Tao Liu Moving target inverse synthetic aperture radar image resolution enhancement based on two‐dimensional block sparse signal reconstruction IET Image Processing Image and video coding Radar equipment, systems and applications Optimisation techniques Interpolation and function approximation (numerical analysis) |
| title | Moving target inverse synthetic aperture radar image resolution enhancement based on two‐dimensional block sparse signal reconstruction |
| title_full | Moving target inverse synthetic aperture radar image resolution enhancement based on two‐dimensional block sparse signal reconstruction |
| title_fullStr | Moving target inverse synthetic aperture radar image resolution enhancement based on two‐dimensional block sparse signal reconstruction |
| title_full_unstemmed | Moving target inverse synthetic aperture radar image resolution enhancement based on two‐dimensional block sparse signal reconstruction |
| title_short | Moving target inverse synthetic aperture radar image resolution enhancement based on two‐dimensional block sparse signal reconstruction |
| title_sort | moving target inverse synthetic aperture radar image resolution enhancement based on two dimensional block sparse signal reconstruction |
| topic | Image and video coding Radar equipment, systems and applications Optimisation techniques Interpolation and function approximation (numerical analysis) |
| url | https://doi.org/10.1049/ipr2.12310 |
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