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A TD-CF preprocessing method of FMCW radar for Dynamic Hand Gesture Recognition

机译:用于动态手势识别的FMCW雷达的TD-CF预处理方法

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Radar-based dynamic gesture recognition has attracted great interest of researchers in the field of human-computer interaction. A very important problem in gesture recognition based on radar is radar echo data preprocessing technique, it can significantly improve hand recognition accuracy. In this paper, we present a Threshold-Denoising and CA-CFAR (TD-CF) method of FMCW radar echo for hand gesture recognition. We first perform a 2D-FFT with a window function on the echo data matrix to deal with spectrum leakage problem and get a Range Doppler Map. An improved wavelet threshold algorithm is designed for noise removal and then a CA-CFAR detector is used to suppress echo data clutter. Experimental results validate that this preprocessing method can effectively remove noise and suppress clutter, which greatly reduce the difficulty of subsequent recognition. We can find obvious movement trend of gestures after TD-CF preprocessing.
机译:基于雷达的动态手势识别在人机交互领域引起了研究人员的极大兴趣。基于雷达的手势识别中一个非常重要的问题是雷达回波数据预处理技术,它可以显着提高手的识别精度。在本文中,我们提出了一种用于手势识别的FMCW雷达回波的阈值去噪和CA-CFAR(TD-CF)方法。我们首先对回波数据矩阵执行带有窗口函数的2D-FFT,以处理频谱泄漏问题,并获得距离多普勒图。设计了一种改进的小波阈值算法来去除噪声,然后使用CA-CFAR检测器抑制回波数据的杂波。实验结果证明,该预处理方法可以有效去除噪声,抑制杂波,大大降低了后续识别的难度。经过TD-CF预处理,我们可以发现手势的明显运动趋势。

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