系统工程与电子技术

• 传感器与信号处理 • 上一篇    下一篇

基于广义S变换的多人微多普勒特征分析

孙忠胜, 王俊, 毕严先, 袁常顺, 张耀天   

  1. (北京航空航天大学电子与信息工程学院, 北京 100191)
  • 出版日期:2014-07-22 发布日期:2010-01-03

Analysis of multihuman microDoppler signatures based #br# on generalized S transform

SUN Zhongsheng, WANG Jun, BI Yanxian, YUAN Changshun, ZHANG Yaotian   

  1. (School of Electronics and Information Engineering, Beihang University, Beijing 100191, China)
  • Online:2014-07-22 Published:2010-01-03

摘要:

微多普勒特征是运动目标的独特特征,可为目标分类识别提供依据。人体行走是典型的非刚体运动,其雷达回波中包含多个频率分量,且分量之间频率重叠严重,因此对其进行微多普勒特征分析难度较大。首先构建人体行走模型及其雷达回波模型,然后以广义S变换为分析工具,对人体主要部位、单人行走和两人行走进行微多普勒特征分析,提出应该以脚部、小腿和躯干部的微多普勒特征作为人体行走识别的主要特征,为后续深入研究人体微多普勒特征奠定了基础。

Abstract:

MicroDoppler signature is a unique signature of an object in motion, and can provide reasons for object classification and recognition. Human walking is a typical nonrigid motion, and there are many components with different frequencies overlapping seriously with each other in its radar echoes. So it is difficult to analyze walking human’s microDoppler signatures. First, the human walking model and its radar echo model are constructed, then the microDoppler signatures of main body parts, single human walking and two human walking are analyzed with the generalized S transform(GST) as the timefrequency analysis tool, and the view that taking the microDoppler signatures of feet, calves, and torsos as the main signatures of human walking recognition is proposed, which lies a foundation for further study of human microDoppler signatures in future.