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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Spaceborne 3-D SAR Tomography for Analyzing Garbled Urban Scenarios: Single-Look Superresolution Advances and Experiments
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Spaceborne 3-D SAR Tomography for Analyzing Garbled Urban Scenarios: Single-Look Superresolution Advances and Experiments

机译:用于分析乱码城市场景的星载3D SAR层析成像:单看超分辨率研究进展和实验

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摘要

Synthetic Aperture Radar Tomography (Tomo-SAR) is an emerging experimental “coherent data combination” mode allowing unprecedented full 3-D imaging of complex urban and infrastructure scenarios with layover (“garbled”) scatterers, exploiting multibaseline interferometric SAR data stacks. Various approaches have been proposed to improve Fourier-based Tomo-SAR elevation beamforming which is affected by unsatisfactory height sidelobe behaviour and resolution, due to the typical low number of baselines with irregular distribution. Among these approaches, height superresolution multilook beamforming techniques proved to posses interesting capabilities, at the cost of operation with reduced horizontal resolution. In this work, a recently proposed knowledge-based baseline interpolation and the Capon and MUSIC superresolution methods are integrated in to a new Tomo-SAR processor able to offer at a low computational burden height superresolution and sidelobe cleaning with single-look data, allowing full resolution operation, as important in urban and other man-made areas. Results are reported with real ERS data.
机译:合成孔径雷达层析成像(Tomo-SAR)是一种新兴的实验性“相干数据组合”模式,可利用多基线干涉SAR数据堆栈,对具有覆盖(“乱码”)散射体的复杂城市和基础设施场景进行前所未有的全3D成像。已经提出了各种方法来改善基于傅里叶的Tomo-SAR高程波束成形,由于典型的基线数量不规则且数量较少,该方法受高度旁瓣行为和分辨率不令人满意的影响。在这些方法中,事实证明,高度超分辨率多视波束形成技术具有令人感兴趣的功能,但以降低水平分辨率的操作为代价。在这项工作中,最近提出的基于知识的基线插值以及Capon和MUSIC超分辨率方法被集成到了新的Tomo-SAR处理器中,该处理器能够以低计算负担的高度提供超分辨率和旁瓣清洗的单眼数据,从而实现分辨率操作,在城市和其他人造区域中同样重要。结果以实际ERS数据报告。

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