首页> 外文会议>Conference on algorithms for synthetic aperture radar imagery XVI; 20090416-17; Orlando, FL(US) >Localization of scattering centers in radar imaging based on sparsity constraints
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Localization of scattering centers in radar imaging based on sparsity constraints

机译:基于稀疏约束的雷达成像散射中心定位

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In radar imaging, for example Inverse Synthetic Aperture Radar (ISAR) imaging, a target can be modeled as a collection of scattering centers in the image domain. A method to improve radar image quality through clutter suppression and localization of scattering centers is presented in this paper. The approach is based on localizing the scattering centers by enforcing sparsity constraints through random compressive sampling of the measured data. Sparsity constraint ratio is chosen as a design parameter to achieve the objective. Results show that significant clutter reduction and improvement in localization of scattering centers are achieved at an optimum sparsity constraint ratio.
机译:在雷达成像中,例如逆合成孔径雷达(ISAR)成像中,可以将目标建模为图像域中散射中心的集合。提出了一种通过杂波抑制和散射中心定位提高雷达图像质量的方法。该方法基于通过对测量数据进行随机压缩采样来实施稀疏性约束来定位散射中心。选择稀疏约束比作为设计参数以达到目的。结果表明,在最佳稀疏约束比下,杂波显着减少,散射中心的定位得到改善。

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