Fast SAR Autofocus Based on Ensemble Convolutional Extreme Learning Machine
Inaccurate Synthetic Aperture Radar (SAR) navigation information will lead to unknown phase errors in SAR data. Uncompensated phase errors can blur the SAR images. Autofocus is a technique that can automatically estimate phase errors from data. However, existing autofocus algorithms either have poor...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-07-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/13/14/2683 |
| _version_ | 1797526113512062976 |
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| author | Zhi Liu Shuyuan Yang Zhixi Feng Quanwei Gao Min Wang |
| author_facet | Zhi Liu Shuyuan Yang Zhixi Feng Quanwei Gao Min Wang |
| author_sort | Zhi Liu |
| collection | DOAJ |
| description | Inaccurate Synthetic Aperture Radar (SAR) navigation information will lead to unknown phase errors in SAR data. Uncompensated phase errors can blur the SAR images. Autofocus is a technique that can automatically estimate phase errors from data. However, existing autofocus algorithms either have poor focusing quality or a slow focusing speed. In this paper, an ensemble learning-based autofocus method is proposed. Convolutional Extreme Learning Machine (CELM) is constructed and utilized to estimate the phase error. However, the performance of a single CELM is poor. To overcome this, a novel, metric-based combination strategy is proposed, combining multiple CELMs to further improve the estimation accuracy. The proposed model is trained with the classical bagging-based ensemble learning method. The training and testing process is non-iterative and fast. Experimental results conducted on real SAR data show that the proposed method has a good trade-off between focusing quality and speed. |
| first_indexed | 2024-03-10T09:25:30Z |
| format | Article |
| id | doaj.art-4ef8a9c66070411e9447caa6ba0ecd44 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T09:25:30Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-4ef8a9c66070411e9447caa6ba0ecd442023-11-22T04:50:52ZengMDPI AGRemote Sensing2072-42922021-07-011314268310.3390/rs13142683Fast SAR Autofocus Based on Ensemble Convolutional Extreme Learning MachineZhi Liu0Shuyuan Yang1Zhixi Feng2Quanwei Gao3Min Wang4School of Artificial Intelligence, Xidian University, Xi’an 710071, ChinaSchool of Artificial Intelligence, Xidian University, Xi’an 710071, ChinaSchool of Artificial Intelligence, Xidian University, Xi’an 710071, ChinaSchool of Artificial Intelligence, Xidian University, Xi’an 710071, ChinaSchool of Electronic Engineering, Xidian University, Xi’an 710071, ChinaInaccurate Synthetic Aperture Radar (SAR) navigation information will lead to unknown phase errors in SAR data. Uncompensated phase errors can blur the SAR images. Autofocus is a technique that can automatically estimate phase errors from data. However, existing autofocus algorithms either have poor focusing quality or a slow focusing speed. In this paper, an ensemble learning-based autofocus method is proposed. Convolutional Extreme Learning Machine (CELM) is constructed and utilized to estimate the phase error. However, the performance of a single CELM is poor. To overcome this, a novel, metric-based combination strategy is proposed, combining multiple CELMs to further improve the estimation accuracy. The proposed model is trained with the classical bagging-based ensemble learning method. The training and testing process is non-iterative and fast. Experimental results conducted on real SAR data show that the proposed method has a good trade-off between focusing quality and speed.https://www.mdpi.com/2072-4292/13/14/2683synthetic aperture radarautofocusensemble learningextreme learning machineconvolutional neural network |
| spellingShingle | Zhi Liu Shuyuan Yang Zhixi Feng Quanwei Gao Min Wang Fast SAR Autofocus Based on Ensemble Convolutional Extreme Learning Machine Remote Sensing synthetic aperture radar autofocus ensemble learning extreme learning machine convolutional neural network |
| title | Fast SAR Autofocus Based on Ensemble Convolutional Extreme Learning Machine |
| title_full | Fast SAR Autofocus Based on Ensemble Convolutional Extreme Learning Machine |
| title_fullStr | Fast SAR Autofocus Based on Ensemble Convolutional Extreme Learning Machine |
| title_full_unstemmed | Fast SAR Autofocus Based on Ensemble Convolutional Extreme Learning Machine |
| title_short | Fast SAR Autofocus Based on Ensemble Convolutional Extreme Learning Machine |
| title_sort | fast sar autofocus based on ensemble convolutional extreme learning machine |
| topic | synthetic aperture radar autofocus ensemble learning extreme learning machine convolutional neural network |
| url | https://www.mdpi.com/2072-4292/13/14/2683 |
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