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Sense-Through-Foliage target detection using UWB radar sensor networks

机译:使用UWB雷达传感器网络的直通树叶目标检测

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摘要

In this paper, we propose two signal processing approaches to detect the target obscured by foliage based on real data collected by an Ultra-wide band (UWB) radar sensor. One is a differential-based four-step signal processing approach that estimates and offsets the impulsive clutter; the other approach employs short-time Fourier transform (STFT) to distinguish the target from foliage clutter. Both of these approaches provide better detection performance compared to the common 2-D image algorithm used for UWB radar. From time to time, due to the significant pulse-to-pulse variability of the foliage clutter, neither differential-based nor STFT approach can detect the target. In this case, we propose radar sensor network (RSN) and a RAKE structure in addition to the previous signal processing approaches for data fusion. The result shows that accurate detection can be achieved. Numerical performances have been analyzed for both cases in terms of probability of detection and probability of false alarm.
机译:在本文中,我们基于超宽带(UWB)雷达传感器收集的真实数据,提出了两种信号处理方法来检测被树叶遮挡的目标。一种是基于差分的四步信号处理方法,该方法可估计和补偿脉冲杂波。另一种方法是使用短时傅立叶变换(STFT)来区分目标和树叶杂波。与用于UWB雷达的普通2-D图像算法相比,这两种方法都提供了更好的检测性能。有时,由于树叶杂波的明显脉冲间差异,基于差分的方法和STFT方法均无法检测到目标。在这种情况下,除了以前的数据融合信号处理方法外,我们还提出了雷达传感器网络(RSN)和RAKE结构。结果表明可以实现准确的检测。已经针对两种情况的检测概率和虚警概率分析了数值性能。

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