Biometrics use an individual’s biological traits for personal identification. Various sensors have been used to obtain these measurements. Microwave biometric scans have recently gained traction as a non-contact technique due to their robustness to environmental lighting and unobtrusiveness. To evaluate microwave signature of human forearm as a biometric modality, an 8-antenna (Wi-Fi) data collection setup was developed and initially tested with foil-wrapped tubes of different geometric cross sections. The system was later evaluated by collecting microwave samples from human volunteers’ forearms and classifying the data, from different antenna subsets, using Support Vector Machines and Naive Bayesian classifiers. Our results show that human identification via microwave signals is possible even with a subset of the above mentioned 8-antenna configuration.

中文翻译：

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前臂对S波段微波散射测量的机器学习分类作为一种新的生物识别技术

生物识别使用个人的生物特征进行个人识别。已经使用各种传感器来获得这些测量值。微波生物特征扫描由于其对环境照明的坚固性和不引人注目性，最近作为一种非接触技术而受到关注。为了评估人类前臂作为生物特征形式的微波信号，开发了8天线（Wi-Fi）数据收集装置，并首先使用具有不同几何横截面的铝箔包裹管进行了测试。随后，通过使用支持向量机和朴素贝叶斯分类器从人类志愿者的前臂收集微波样本并对不同天线子集的数据进行分类，从而对该系统进行了评估。