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An image quality improvement method under sparse array and small bandwidth in MIMO IR-UWB imaging system

机译:MIMO IR-UWB成像系统中稀疏阵列和小带宽下的图像质量改善方法

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In this paper, we proposed a new algorithm to improve the image quality degradation due to sparse array topology and small fractional bandwidth of commercial radar chip in two-dimensional (2-D) multiple-input-multiple-output (MIMO) impulse radio ultra-wideband (IR-UWB) array imaging system. The new algorithm, which adds a clustering concept and signal windowing method to the existing delay-and-sum (DAS) algorithm, enables short range imaging in a practical environment with fewer antenna placement and fractional bandwidth of less than 100%. Experiments were performed on human mannequin targets using a sparse cross array topology with an antenna spacing of 2.0λ and a commercial IR UWB radar chip with a fractional bandwidth of 34%. The test results show that several spurious images and image quality degradation, including grating lobes, occurring in the conventional DAS imaging algorithm are completely improved in the new algorithm. Therefore, the results of this paper show that the short-range IR-UWB radar imaging system may be used in real commercial applications in the future.
机译:在本文中,我们提出了一种新的算法来改善二维(2-D)多输入多输出(MIMO)脉冲无线电超模式中由于稀疏阵列拓扑和商用雷达芯片的小分数带宽导致的图像质量下降宽带(IR-UWB)阵列成像系统。新算法将聚类概念和信号开窗方法添加到现有的延迟和(DAS)算法中,可在实际环境中以较少的天线放置和小于100%的分数带宽实现短距离成像。使用天线间距为2.0λ的稀疏交叉阵列拓扑结构和分数带宽为34%的商用IR UWB雷达芯片,对人体模型目标进行了实验。测试结果表明,新算法完全改善了常规DAS成像算法中出现的一些杂散图像和图像质量下降,包括光栅波瓣。因此,本文的结果表明,短程IR-UWB雷达成像系统可能会在未来的实际商业应用中使用。

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