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2021-06-16

Human Multicomponent Micro-Doppler Signals Separation Based on a Novel Local Time-Frequency Sparse Reconstruction Method

By Zhongfei Ni and Bin-Ke Huang
Progress In Electromagnetics Research C, Vol. 113, 137-146, 2021
doi:10.2528/PIERC21041202

Abstract

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.

Citation


Zhongfei Ni and Bin-Ke Huang, "Human Multicomponent Micro-Doppler Signals Separation Based on a Novel Local Time-Frequency Sparse Reconstruction Method," Progress In Electromagnetics Research C, Vol. 113, 137-146, 2021.
doi:10.2528/PIERC21041202
http://www.jpier.org/PIERC/pier.php?paper=21041202

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