| 基于变分模型的阵列三维SAR最优DEM重建方法 |
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| 引用本文： | 师君,张晓玲,韦顺军,向高,杨建宇.基于变分模型的阵列三维SAR最优DEM重建方法[J].雷达学报,2015,4(1):20-28. |
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| 作者姓名： | 师君 张晓玲 韦顺军 向高 杨建宇 |
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| 作者单位： | (电子科技大学电子工程学院 成都 611731) |
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| 基金项目： | 国家自然科学基金(61101170);高分专项青年创新基金(GFZX04060103-5-25);博士后基金(2013M530395,2014T70857)资助课题 |
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| 摘 要： | 由于具备了下视3维成像能力，阵列3维SAR在地形测绘、灾害监测等领域具有广泛的应用前景。但是，载机平台尺寸的限制使得其阵列方向分辨率远远低于距离向和航迹向，严重制约了阵列3维SAR系统整体性能的提升。目前研究主要针对3维SAR图像的稀疏性，采用稀疏重建方法提高其在阵列方向的分辨率。稀疏重建模型在求解过程中丢失了数字高程图(DEM)所具有的单值性、连续性等特征。为了克服稀疏重建模型存在的问题，该文提出了基于变分模型的阵列3维SAR最优DEM重建方法，该方法直接将DEM图作为最优化目标，通过寻找最优化DEM图和对应的散射系数，实现最小二乘意义下的最优DEM重建。仿真结果表明，该方法可以实现各种地形(山区、城市)的稳健DEM增强，其性能远优于OMP算法和正则化方法。
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| 关 键 词： | 阵列3维SAR 变分模型 最优DEM重建 最小二乘准则 |
| 收稿时间： | 2014-11-20 |
An Optimal DEM Reconstruction Method for Linear Array Synthetic Aperture Radar Based on Variational Model |
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| Shi Jun;Zhang Xiao-ling;Wei Shun-jun;Xiang Gao;Yang Jian-yu.An Optimal DEM Reconstruction Method for Linear Array Synthetic Aperture Radar Based on Variational Model[J].Journal of Radars,2015,4(1):20-28. |
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| Authors: | Shi Jun;Zhang Xiao-ling;Wei Shun-jun;Xiang Gao;Yang Jian-yu |
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| Affiliation: | (School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China) |
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| Abstract: | Downward-looking Linear Array Synthetic Aperture Radar (LASAR) has many potential applications in the topographic mapping, disaster monitoring and reconnaissance applications, especially in the mountainous area. However, limited by the sizes of platforms, its resolution in the linear array direction is always far lower than those in the range and azimuth directions. This disadvantage leads to the blurring of Three-Dimensional (3D) images in the linear array direction, and restricts the application of LASAR. To date, the research on 3D SAR image enhancement has focused on the sparse recovery technique. In this case, the one-to-one mapping of Digital Elevation Model (DEM) brakes down. To overcome this, an optimal DEM reconstruction method for LASAR based on the variational model is discussed in an effort to optimize the DEM and the associated scattering coefficient map, and to minimize the Mean Square Error (MSE). Using simulation experiments, it is found that the variational model is more suitable for DEM enhancement applications to all kinds of terrains compared with the Orthogonal Matching Pursuit (OMP)and Least Absolute Shrinkage and Selection Operator (LASSO) methods. |
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