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3D imaging for underfoliage targets using L-band Multi-Baseline PolInSAR Data and sparse estimation methods

机译:使用L波段多基线PolInSAR数据和稀疏估计方法对植被不足目标进行3D成像

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SAR imaging of concealed targets beneath the canopies has to face a complex mixture of diverse scattering mechanisms. To characterize this complex scattering environment, nonparametric tomographic estimators are more robust to focusing artefacts but limited in resolution. Parametric tomographic estimators provide better vertical resolution but fail to adequately characterize continuously distributed volumetric scatterers such as forest canopies. To overcome these limitations, this paper addresses a new wavelet-based sparse estimation method for 3D imaging and characterization for underfoliage objects. The effectiveness of this new approach is demonstrated by using L-band Multi-Baseline PolInSAR Data over Dornstetten, Germany.
机译:在檐篷下方隐藏目标的SAR成像必须面对不同的散射机制的复杂混合物。为了表征这种复杂的散射环境,非参数断层估计对于聚焦的人工制品更加强大,但在分辨率中有限。参数断层估计值提供更好的垂直分辨率,但不能充分表征连续分布的体积散射仪,例如森林檐篷。为了克服这些限制,本文解决了一种新的基于小波的稀疏估计方法,用于底层对象的3D成像和表征。通过使用Dornstetten,德国Dornstetten的L波段多基线Polinsar数据来证明这种新方法的有效性。

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