基于人体通信的生物特征身份识别方法研究  

Research on biometric identification method based on human body communication

作　　者：吴秋雯 廖薇 Wu Qiuwen;Liao Wei(School of Electronic and Electrical Engineering,Shanghai University of Engineering Science,Shanghai 201620,China)

机构地区：[1]上海工程技术大学电子电气工程学院,上海201620

出　　处：《电子测量与仪器学报》2022年第5期113-119,共7页Journal of Electronic Measurement and Instrumentation

基　　金：国家自然科学基金(62001282)项目资助。

摘　　要：由于人体通信技术发展迅速且应用前景广阔,提出一种基于人体通信技术的生物特征身份识别方法。在适合人体通信的UWB频段和HBC频段下,将人体通信链路的路径损耗作为生物特征。首先根据不同链路的测量值,使用支持向量机进行身份识别;再使用带有不同核函数的C-SVM和Nu-SVM方法在11条链路的数据集下进行身份识别;最后选取8~10 GHz的UWB子频段进行识别提高计算速度。结果表明,链路通信距离越长,识别率越高。带高斯核的C-SVM在UWB频段下的识别效果最好,识别率达96.41%、AUC为0.9991以及0.0172%的EER。通过选取子频段将计算时间降低到0.142 s,速度得到明显提高。Due to the rapid development of human body communication technology and broad application prospects,this paper proposes a biometric identification method based on human body communication technology.In the UWB frequency band and HBC frequency band suitable for human body communication,the path loss of the human body communication link is used as a biological feature.First,use the support vector machine for identification according to the measured values of different links;then use the C-SVM and Nu-SVM methods with different kernel functions for identification under the data set of 11 links;finally select 8~10 GHz UWB sub-band is recognized to improve the calculation speed.The results show that:the longer the link communication distance,the higher the recognition rate.The C-SVM with Gaussian kernel has the best recognition effect in the UWB frequency band,with a recognition rate of 96.41%,AUC of 0.9991 and EER of 0.0172%.By selecting the sub-band to reduce the calculation time to 0.142 s,the speed is significantly improved.

关 键 词：路径损耗 人体区域通信 生物识别 支持向量机 

分 类 号：TN915[电子电信—通信与信息系统]