关键词: 超宽带雷达, 人体姿态识别, 深度学习, 支持向量机, 卷积神经网络

Abstract:

Compared with the traditional camera, the use of Ultra-Wideband（UWB） radar for human posture recognition is not only low environmental requirements, high recognition rate and can better solve the problems of blind spots and easy to leak privacy in the camera. Combined with the characteristics of the UWB radar system, the common ultra-wideband pulse signals are analyzed in detail. According to the current research frontier, the traditional machine learning methods and deep learning methods of human posture recognition by UWB radar are analyzed, and the principle and each model’s limitation of the representative Support Vector Machine（SVM）and Convolutional Neural Networks（CNN） are analyzed and discussed in combination with the specific literature. The general model of UWB radar human posture recognition is proposed, the problems that need to be solved urgently in human posture recognition by UWB radar are analyzed and its future development direction is prospected.

Key words: Ultra-Wideband（UWB） radar, human posture recognition, deep learning, Support Vector Machine（SVM）, Convolutional Neural Networks（CNN）