Human multicomponent micro-doppler signals separation based on a novel local time-frequency sparse reconstruction method

被引：0
作者：
Ni Z. [1 ]
Huang B. [1 ]
机构：
[1] School of Information and Communication Engineering, Xi’an Jiaotong University, Xi’an
来源：
Progress In Electromagnetics Research C | 2021年 / 113卷
基金：
中国国家自然科学基金;
关键词：
Signal reconstruction - Separation;
D O I：
10.2528/PIERC21041202
中图分类号：
学科分类号：
摘要：
—The use of radar micro-Doppler (m-D) signatures for human activities classification, surveillance and healthcare has become a hot topic in recent years. While m-D signals are always multicomponent, it is necessary to separate them into mono-components signals associated with individual body parts for easier features analysis and extraction. In this paper, a novel method called local time-frequency sparse reconstruction (LTFSR) is proposed to iteratively extract and separate m-D components one by one in a descending intensity order from a time-frequency (T-F) representation. For the current strongest m-D component, we first estimate its instantaneous frequency (IF) by dividing the signal into short overlapping time intervals and selecting the best matching chirp atom to approximate the local frequency in each time interval based on matching pursuit. Then, a T-F filtering is used to extract and remove the strongest component from the multicomponent signal. Repeat the above steps until all m-D components are separated. Simulations are given to validate the effectiveness and robustness of the proposed method. © 2021, Electromagnetics Academy. All rights reserved.
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收藏
页码：137 / 146
页数：9
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