SAR processing with zeros

带零的 SAR 处理

• 批准号: EP/H012370/1
• 负责人: Mike Davies
• 金额: $ 13.52万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2010
• 资助国家: 英国
• 起止时间: 2010 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FH012370%2F1
• 关键词: SAR; processing; zeros

Synthetic Aperture Radar (SAR) provides the military with an extremely valuable means of remote imaging and plays an important role in target detection. SAR works by measuring the electromagnetic signal reflections from the ground. Processing the raw received data to generate the image is usually performed using linear frequency domain techniqes such as the Polar Format Algorithm. However when there is missing data, or when gaps in the data (either spatially or spectrally) are introduced the performance of such estimators deteriorates considerably. The resulting images exhibit distortion and aliasing artefacts.Recently a new theory for signal reconstruction, called compressed sensing, has emerged. It explores the extent to which ill-posed sampling problems such as those discussed above can be made well-posed through the inclusion of strong signal models. These techniques have already been successfully applied to SAR image reconstruction for target detection and super resolution. The broad aim of this proposal is to explore the application of compressed sensing reconstruction techniques to SAR image formation when spatial and/or frequency notches are introduced into the transmitted/received signals. Ultimately we hope to gain a general understanding of the limits to which the SAR data acquisition system can be so modified without incurring serious performance degradation.

合成孔径雷达（SAR）为军事领域提供了一种极具价值的远程成像手段，在目标检测中发挥着重要作用。合成孔径雷达的工作原理是测量从地面反射的电磁信号。处理原始接收数据以生成图像通常使用线性频域技术（诸如极坐标格式算法）来执行。然而，当有丢失的数据，或当间隙的数据（无论是空间或频谱）被引入的性能，这样的估计大大恶化。最近出现了一种新的信号重构理论，称为压缩感知。它探讨了通过包含强信号模型可以在多大程度上使上述不适定采样问题变得适定。这些技术已成功地应用于SAR图像重建中的目标检测和超分辨率。该建议的主要目的是探索压缩感知重建技术的应用，SAR图像形成时，空间和/或频率陷波被引入到发送/接收信号。最后，我们希望获得一个一般性的了解的限制，可以这样修改的SAR数据采集系统，而不会引起严重的性能下降。

项目成果

Iterative image formation using fast (Re/Back)-projection for spotlight-mode SAR

使用快速（后/后）投影进行聚光模式 SAR 的迭代成像

• DOI: 10.1109/radar.2011.5960654
• 发表时间: 2011
• 作者: Kelly S

Processing SAR data with gaps in the aperture: a compressed sensing perspective

• 发表时间: 2010
• 作者: G. Rilling;Chaoran Du;Michael Davies;B. Mulgrew

RFI suppression and sparse image formation for UWB SAR

UWB SAR 的 RFI 抑制和稀疏图像形成

• 发表时间: 2013
• 期刊: 14th International Radar Symposium (IRS) 2013
• 作者: Kelly, S

Auto-focus for Compressively Sampled SAR

• 发表时间: 2012-05
• 作者: Steven Kelly;Mehrdad Yaghoobi;Michael Davies

Sparsity-Based Autofocus for Undersampled Synthetic Aperture Radar

• DOI: 10.1109/taes.2014.120502
• 发表时间: 2014-04-01
• 期刊: IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
• 影响因子: 4.4
• 作者: Kelly, Shaun;Yaghoobi, Mehrdad;Davies, Mike
• 通讯作者: Davies, Mike