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Extended Targets Modelling and Block Agnostic Sparse Reconstruction in Through-the-Wall Radar Imaging: A Different Perspective

机译:穿墙雷达成像中的扩展目标建模和不可知性的稀疏重建:不同的观点

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摘要

A common target model in through-the-wall radar (TWRI) imaging literature obeys the point target (PT) assumption in which, a target is hypothesized to occupy a single pixel. Unlike PTs, the received signal reflected from extended target (ET) is an integration of the scattered signals from various parts of the same target. For high resolution images, a generalized model is needed to encompass the ETs. The ET modelling and reconstruction under compressive sensing (CS) framework have not been studied comprehensively yet. Existing reconstruction methods for ETs assume that when the scene is vectorized, target pixels form blocks with constant block sizes, also, assume that the size and number of the blocks and their sizes are known in priori and they follow Gaussian distributions. These assumptions rarely mimic the practical TWRI scenarios. In this paper, we suggest a different but realistic ET reconstruction approach based on agnostic block sparsity. The algorithm does not impose any assumption on the length, number, or the distribution of the blocks.? Results based on MATLAB simulation and experimental data show the effectiveness of the proposed reconstruction approach.
机译:穿墙雷达(TWRI)成像文献中的常见目标模型遵循点目标(PT)的假设,在该假设中,假设目标占据一个像素。与PT不同,扩展目标(ET)反射的接收信号是来自同一目标各个部分的散射信号的积分。对于高分辨率图像,需要一个通用模型来包含ET。在压缩感知(CS)框架下的ET建模和重构尚未得到全面研究。现有的用于ET的重建方法假设当场景被矢量化时,目标像素形成具有恒定块大小的块,还假设块的大小和数量以及它们的大小是先验的,并且它们遵循高斯分布。这些假设很少模仿实际的TWRI方案。在本文中,我们提出了一种基于不可知块稀疏性的不同但现实的ET重建方法。该算法不对块的长度,数量或分布施加任何假设。基于MATLAB仿真和实验数据的结果表明了所提出的重建方法的有效性。

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