| 宋亚磊.SAR 图像超分辨重构及在目标识别中的应用[J].电子测量与仪器学报,2020,34(10):164-170 |
| SAR 图像超分辨重构及在目标识别中的应用 |
| Super-resolution reconstruction of SAR images with application to target recognition |
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| DOI： |
| 中文关键词: 合成孔径雷达 目标识别 超分辨率重构 属性散射中心模型 联合稀疏表示 |
| 英文关键词:synthetic aperture radar target recognition super-resolution reconstruction attributed scattering center model joint
sparse representation |
| 基金项目:河南省社会科学普及规划项目(0103)资助 |
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| 中文摘要: |
| 针对合成孔径雷达(SAR)目标识别问题,设计了图像超分辨重构算法并进行应用。 基于属性散射中心模型对 SAR 图
像进行参数估计以及高分辨率构造,获得原始图像的多分辨率描述。 采用联合稀疏表示对原始图像及其高分辨率表示进行表
征,考察它们的内在关联。 最终,根据整体重构误差判定测试样本的目标类别。 在 MSTAR 数据集上的实验结果表明了提出方
法的有效性。 |
| 英文摘要: |
| The super-resolution reconstruction algorithm is applied to synthetic aperture radar (SAR) target recognition. The parameters
of SAR images are estimated based on the attributed scattering center model for high-resolution reconstruction, thus generating the multiresolution representations of the original images. The joint sparse representation is employed to represent the original image together with
its high-resolution representations, thus considering their inner correlations. Finally, the target label is determined based on the total
reconstruction errors. The experimental results on the MSTAR dataset confirm the validity of the proposed method. |
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