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Sparsity-Based Multipath Exploitation for Through-the-Wall Radar Imaging

机译:基于稀疏性的全程雷达成像多径开发

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摘要

In this PhD thesis sparsity-based multipath exploitation methods are developed for through-the-wall radar imaging. This imaging modality uses the radar principle to reveal targets in a scene obscured by, for example, a building wall. The scattered electromagnetic wave returning from a target may reach the receiver via different propagation paths which is called multipath. This creates ambiguities in the measurements provoking unwanted ghost targets in the image. For image reconstruction, the aforementioned issue can be resolved by utilizing the sparsity of the scene. Hence, compressive sensing is employed to recover the positions of valid targets while suppressing ghosts. As an additional benefit, fewer measurements are required for image reconstruction.\ud\udAn additive multipath signal model is developed that includes returns from the targets of interest and the building structure. \udIncorporating the model in the image reconstruction methods allows exploitation of additional energy contained in secondary reflections.\udMultipath exploitation of stationary and moving targets employs compressive sensing.\udTherein, both sparsity and the structure originating from multipath propagation are utilized in the reconstruction problem. Moreover, the Doppler information contained in indirect propagation paths is investigated. A computationally efficient two-step approach is proposed that localizes the targets first. As a second step, the velocity vector is estimated from multipath Doppler. \udThe scenario is extended to multiple compact radar modules, distributed around the scene. \udThe reconstruction performance for closely-spaced and widely-separated placement is analyzed.\ud\udThis work also deals with adverse effects on the imaging results caused by signal interaction with the building structure.\udReturns from the front wall, so-called wall clutter, are normally suppressed using a pre-processing step. A joint wall signal and target image reconstruction approach is proposed that renders prior wall clutter mitigation unnecessary. \udFurthermore, the case of imperfect prior knowledge of the building layout is discussed. It is shown that errors in the position of interior walls lead to complete failure of multipath exploitation. The proposed joint wall position estimation and image reconstruction procedure can deal with uncertainties in the building layout.\ud\udAll proposed methods are evaluated using simulated as well as measured data from semi-controlled laboratory experiments.
机译:在此博士学位论文中,开发了基于稀疏性的多路径开发方法,用于穿墙雷达成像。这种成像方式使用雷达原理来揭示场景中的目标,例如被建筑物墙壁遮挡的场景。从目标返回的散射电磁波可能会通过称为多径的不同传播路径到达接收器。这会在测量中产生歧义,从而引起图像中不需要的重影目标。对于图像重建,可以通过利用场景的稀疏性来解决上述问题。因此,在抑制重影的同时,采用压缩感测来恢复有效目标的位置。另一个好处是,图像重建所需的测量次数更少。\ ud \ ud开发了一个附加的多径信号模型,该模型包括感兴趣目标和建筑结构的返回。 \ ud将模型合并到图像重建方法中可以利用二次反射中包含的额外能量。\ ud对固定目标和运动目标的多径利用采用压缩感知。\ ud其中,稀疏性和源自多径传播的结构都用于重建问题。此外,还研究了间接传播路径中包含的多普勒信息。提出了一种计算有效的两步法,该方法首先定位目标。第二步,从多径多普勒估计速度矢量。 \ ud该方案扩展到了分布在现场的多个紧凑型雷达模块。 \ ud分析了在空间狭窄且间隔较大的位置上的重建性能。\ ud \ ud这项工作还处理了由于信号与建筑结构相互作用而对成像结果产生的不利影响。\ ud从前墙返回,即所谓的墙通常使用预处理步骤来抑制混乱。提出了一种联合壁信号和目标图像重建方法,该方法使得不需要先前的壁杂波减轻。 \ ud此外,讨论了建筑物布局的先验知识不完善的情况。结果表明,内墙位置的错误会导致多路径开发的完全失败。提出的联合墙位置估计和图像重建程序可以处理建筑物布局中的不确定性。\ ud \ ud所有提议的方法均使用来自半控制实验室实验的模拟数据和实测数据进行评估。

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  • 作者

    Leigsnering, Michael;

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  • 年度 2016
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  • 原文格式 PDF
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