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Automatic human micro-Doppler signature separation by Hough transform

机译:通过霍夫变换自动进行人体微多普勒签名分离

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The micro-Doppler signature is one of the most prominent information for target classification and identification. As Hough transform (HT) is an efficient tool for detecting weak straight target traces in the image, an HT based algorithm is proposed for micro-Doppler signature separation of multiple persons. Few seconds data is processed at one time to ensure human motion traces approximate to straight lines in the radar slow time-range image. Taking HT to the slow time-range image, each human's motion trace can be recovered through recursively searching the peaks in HT space. Applying time-frequency transform to the range cells around each recovered line, the human micro-Doppler signature can be achieved and separated. Experimental results are given to illustrate the validity of the proposed algorithm.
机译:微多普勒签名是目标分类和识别最重要的信息之一。由于霍夫变换(HT)是检测图像中较弱的直线目标轨迹的有效工具,因此提出了一种基于HT的多人微多普勒签名分离算法。一次可以处理几秒钟的数据,以确保人体运动轨迹近似于雷达慢速时域图像中的直线。将HT带到慢速的时间范围图像,可以通过递归搜索HT空间中的峰值来恢复每个人的运动轨迹。将时频变换应用于每条恢复线周围的距离单元,可以实现并分离人类微多普勒信号。实验结果表明了该算法的有效性。

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