Person Identification Based on Micro-Doppler Signatures of Sit-to-Stand and Stand-to-Sit Movements Using a Convolutional Neural Network
Person Identification Based on Micro-Doppler Signatures of Sit-to-Stand and Stand-to-Sit Movements Using a Convolutional Neural Network
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DOI：
10.1109/lsens.2020.2975219
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发表时间：
2020-02
影响因子：
2.8
通讯作者：
K. Saho;Kei Inuzuka;Keitaro Shioiri
中科院分区：
文献类型：
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作者：
K. Saho;Kei Inuzuka;Keitaro Shioiri
这封信提出了一种基于坐到站和站到坐运动的人识别方法，使用微多普勒雷达测量和卷积神经网络（CNN）。两个24 ghz微型多普勒雷达系统将被放置在参与者的正上方或正后方，用于测量10名参与者从坐到站和从站到坐的运动。将雷达接收到的信号进行短时傅里叶变换，生成微多普勒特征图像。生成的图像将作为cnn的输入，用于训练和评估目的。实验验证了该方法通过测量人们从坐到站和从站到坐的动作来准确识别人的能力。使用放置在参与者上方的雷达数据，从坐到站和从站到坐的识别精度分别为93.6%和94.9%，而将雷达放置在参与者身后时，从坐到站的识别精度为92.9%，从站到坐的识别精度为93.9%。所得结果将证明，两种运动速度的水平和垂直方向都包含可用于识别个体的信息，并且这些信息可以通过微多普勒雷达系统获得。
This letter presents a method for person identification based on sit-to-stand and stand-to-sit movements using micro-Doppler radar measurements and a convolutional neural network (CNN). Two 24-GHz micro-Doppler radar systems placed directly above or behind participants will be used to measure the sit-to-stand and stand-to-sit movements of 10 participants. Images of the micro-Doppler signatures will be generated by subjecting the signals received by the radar to short-time Fourier transform. The generated images will then be used as input for the CNNs for training and evaluation purposes. The experiments verified the ability of the method to accurately identify people by measuring both their sit-to-stand and stand-to-sit movements. The identification accuracies for the sit-to-stand and stand-to-sit measurements were 93.6% and 94.9%, respectively, using the data of the radar placed above the participant, whereas the accuracy when placing the radar behind the participant was 92.9% for the sit-to-stand and 93.9% for the stand-to-sit movements. The obtained results will prove that both the horizontal and vertical directions of the velocities of both movements include information that can be used to identify individuals, and this information can be obtained with micro-Doppler radar systems.