| 基于稀疏空间谱估计的星载SAR DBF算法 |
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| 引用本文： | 叶沙琳,张永,杨桃丽,李威.基于稀疏空间谱估计的星载SAR DBF算法[J].上海航天,2018(6):65-70. |
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| 作者姓名： | 叶沙琳 张永 杨桃丽 李威 |
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| 作者单位： | 上海卫星工程研究所,上海 201109,电子科技大学 资源与环境学院,四川 成都 611731,电子科技大学 资源与环境学院,四川 成都 611731,上海卫星工程研究所,上海 201109 |
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| 基金项目： | 国家自然科学基金(61601090)；上海航天科技创新基金(SAST2016037) |
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| 摘 要： | 针对星载合成孔径雷达(SAR)系统利用俯仰向数字波束形成(DBF)技术接收场景回波时受地形的影响,会出现波束指向偏差的问题,提出了基于稀疏空间谱估计的星载SAR数字波束形成方法。该方法将目标场景高程估计问题转换为波达方向估计问题,考虑到回波信号的稀疏性,进而等效为稀疏空间谱估计问题,然后利用凸优化方法求解得到目标波达方向。最后,仿真实验验证了该方法的有效性,结果表明该方法可以降低传统自适应方法受小样本和低信噪比影响的限制,实现复杂地形下的正确波束指向,保证回波信号的接收增益。
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| 关 键 词： | 星载合成孔径雷达 稀疏空间谱估计 数字波束形成 回波信号 |
| 收稿时间： | 2018/6/23 0:00:00 |
| 修稿时间： | 2018/11/11 0:00:00 |
An Algorithm for Spaceborne SAR DBF Based on Sparse Spatial Spectrum Estimation |
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| YE Shalin,ZHANG Yong,YANG Taoli and LI Wei.An Algorithm for Spaceborne SAR DBF Based on Sparse Spatial Spectrum Estimation[J].Aerospace Shanghai,2018(6):65-70. |
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| Authors: | YE Shalin ZHANG Yong YANG Taoli and LI Wei |
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| Affiliation: | Shanghai Institute of Satellite Engineering, Shanghai 201109, China,School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China,School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, Sichuan, China and Shanghai Institute of Satellite Engineering, Shanghai 201109, China |
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| Abstract: | In order to solve the problem that the imaging terrain will cause beam mispointing for spaceborne synthetic aperture radar (SAR) systems when the digital beamforming (DBF) technique in elevation is adopted, a novel DBF algorithm based on sparse spatial spectrum estimation is proposed in this paper. The estimation of target elevation is converted into the estimation of direction of arrival (DOA) angles. Considering the sparsity of the receiving signals, the estimation problem can also be converted into the sparse spatial spectrum estimation problem, which can be solved by the convex optimization method. Finally, the simulation results verify the effectiveness of this method. Compared to traditional adaptive methods, the proposed method can realize the accurate beam pointing and high beam gain in the complex terrain with low sensitivity to SNR and a small number of snapshots. |
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| Keywords: | synthetic aperture radar(SAR) sparse spatial spectrum estimation digital beamforming(DBF) receiving signal |
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