Verification of Complex Image Based Sparse SAR Imaging Method on GaoFen-3 Dataset
Sparse signal processing-based Synthetic Aperture Radar (SAR) imaging, also known as sparse SAR imaging, is the main research direction of sparse microwave imaging theory. Compared with a conventional SAR system, sparse SAR imaging radar has significant potential to improve imaging performance. Howe...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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China Science Publishing & Media Ltd. (CSPM)
2020-02-01
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| Series: | Leida xuebao |
| Subjects: | |
| Online Access: | http://radars.ie.ac.cn/article/doi/10.12000/JR19092?viewType=HTML |
| _version_ | 1797428637614473216 |
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| author | BI Hui ZHANG Bingchen HONG Wen WU Yirong |
| author_facet | BI Hui ZHANG Bingchen HONG Wen WU Yirong |
| author_sort | BI Hui |
| collection | DOAJ |
| description | Sparse signal processing-based Synthetic Aperture Radar (SAR) imaging, also known as sparse SAR imaging, is the main research direction of sparse microwave imaging theory. Compared with a conventional SAR system, sparse SAR imaging radar has significant potential to improve imaging performance. However, because it requires heavy computations, the application of sparse SAR imaging in large-scene recovery has become difficult, which restricts its further applications. Additionally, complex SAR images, rather than raw data, are usually used for data archiving due to a number of reasons such as data copyright and system
confidentiality. Therefore, it is worthwhile to study how sparse imaging can be achieved using only Matched Filtering (MF) recovered complex images with less computational cost. GaoFen-3 is China’s first 1-m resolution multi-polarization C-band satellite. It has a high-resolution, wide swath imaging ability and hence plays an important role in disaster monitoring and ocean surveillance applications. In this paper, we introduce a complex image-based sparse SAR imaging method to process GaoFen-3 complex image data and improve image performance. Experimental results show that the sparse imaging results have lower sidelobes, higher signal-toclutter and noise ratio, and better target distinguishing ability compared with inputted images. Additionally, sparse imaging can effectively preserve the statistical distribution and phase information of images that makes the recovered GaoFen-3 sparse image-based applications such as interferometric synthetic aperture radar and constant false alarm ratio detection possible. |
| first_indexed | 2024-03-09T09:01:46Z |
| format | Article |
| id | doaj.art-0599f96033e1452481b5b9a968c6160b |
| institution | Directory Open Access Journal |
| issn | 2095-283X 2095-283X |
| language | English |
| last_indexed | 2024-03-09T09:01:46Z |
| publishDate | 2020-02-01 |
| publisher | China Science Publishing & Media Ltd. (CSPM) |
| record_format | Article |
| series | Leida xuebao |
| spelling | doaj.art-0599f96033e1452481b5b9a968c6160b2023-12-02T11:21:37ZengChina Science Publishing & Media Ltd. (CSPM)Leida xuebao2095-283X2095-283X2020-02-019112313010.12000/JR19092Verification of Complex Image Based Sparse SAR Imaging Method on GaoFen-3 DatasetBI Hui0ZHANG Bingchen1HONG Wen2WU Yirong3①(College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)②(Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China)②(Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China)②(Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China)Sparse signal processing-based Synthetic Aperture Radar (SAR) imaging, also known as sparse SAR imaging, is the main research direction of sparse microwave imaging theory. Compared with a conventional SAR system, sparse SAR imaging radar has significant potential to improve imaging performance. However, because it requires heavy computations, the application of sparse SAR imaging in large-scene recovery has become difficult, which restricts its further applications. Additionally, complex SAR images, rather than raw data, are usually used for data archiving due to a number of reasons such as data copyright and system confidentiality. Therefore, it is worthwhile to study how sparse imaging can be achieved using only Matched Filtering (MF) recovered complex images with less computational cost. GaoFen-3 is China’s first 1-m resolution multi-polarization C-band satellite. It has a high-resolution, wide swath imaging ability and hence plays an important role in disaster monitoring and ocean surveillance applications. In this paper, we introduce a complex image-based sparse SAR imaging method to process GaoFen-3 complex image data and improve image performance. Experimental results show that the sparse imaging results have lower sidelobes, higher signal-toclutter and noise ratio, and better target distinguishing ability compared with inputted images. Additionally, sparse imaging can effectively preserve the statistical distribution and phase information of images that makes the recovered GaoFen-3 sparse image-based applications such as interferometric synthetic aperture radar and constant false alarm ratio detection possible.http://radars.ie.ac.cn/article/doi/10.12000/JR19092?viewType=HTMLsynthetic aperture radar (sar)sparse imaginggaofen-3regularization |
| spellingShingle | BI Hui ZHANG Bingchen HONG Wen WU Yirong Verification of Complex Image Based Sparse SAR Imaging Method on GaoFen-3 Dataset Leida xuebao synthetic aperture radar (sar) sparse imaging gaofen-3 regularization |
| title | Verification of Complex Image Based Sparse SAR Imaging Method on GaoFen-3 Dataset |
| title_full | Verification of Complex Image Based Sparse SAR Imaging Method on GaoFen-3 Dataset |
| title_fullStr | Verification of Complex Image Based Sparse SAR Imaging Method on GaoFen-3 Dataset |
| title_full_unstemmed | Verification of Complex Image Based Sparse SAR Imaging Method on GaoFen-3 Dataset |
| title_short | Verification of Complex Image Based Sparse SAR Imaging Method on GaoFen-3 Dataset |
| title_sort | verification of complex image based sparse sar imaging method on gaofen 3 dataset |
| topic | synthetic aperture radar (sar) sparse imaging gaofen-3 regularization |
| url | http://radars.ie.ac.cn/article/doi/10.12000/JR19092?viewType=HTML |
| work_keys_str_mv | AT bihui verificationofcompleximagebasedsparsesarimagingmethodongaofen3dataset AT zhangbingchen verificationofcompleximagebasedsparsesarimagingmethodongaofen3dataset AT hongwen verificationofcompleximagebasedsparsesarimagingmethodongaofen3dataset AT wuyirong verificationofcompleximagebasedsparsesarimagingmethodongaofen3dataset |