题目：Through-Wall Detection of Human Being's Movement by UWB Radar

摘要：Ultrawideband (UWB) radar technology has emerged as one of the preferred choices for through-wall detection due to its high range resolution and good penetration. The resolution is a result of high bandwidth of UWB radar and helpful for better separation of multiple targets in complex environment. Detection of human targets through a wall is interesting in many applications. One significant characteristic of human is the periodic motion, such as breathing and limb movement. In this talk, we apply the UWB radar system in through-wall human detection and present the methods based on fast Fourier transform and S transform to detect and identify the human’s life characteristic. In particular, we can extract the center frequencies of life signals and locate the position of human targets from experimental data with high accuracy. Compared with other research studies in through-wall detection, this letter is concentrated in the processing and identifying of the life signal under strong clutter. It has a high signal-to-noise ratio and simpler to implement in complex environment detection. We can use the method to search and locate the survivor trapped under the building debris during earthquake, explosion, or fire.

简介：孙继广教授，美国密歇根科技大学（Michigan Technological University）数学系终身教授。孙老师1996年本科毕业于清华大学数学系，2005年博士毕业于美国特拉华大学数学系，师从著名计算数学专家Peter Monk教授，主要研究领域为偏微分方程的数值方法，波动方程反散射问题和特征值问题的有限元方法。孙老师已在Inverse Problems, SIAM J. on Scientific Computing等期刊发表高水平论文40余篇，出版学术专著一本。