Library
local_library Home Repository

Radar-based Human Activity Classification with Cyclostationarity

Conference paper (2021)

Authors

Yaxin Du University of Electronic Science and Technology of China
Jipeng Li University of Electronic Science and Technology of China
Zhouyixian Li University of Electronic Science and Technology of China
Ran Yu University of Electronic Science and Technology of China
Antonio Napolitano Centro Direzionale Isola C4
Francesco Fioranelli Microwave Sensing, Signals & Systems
Julien Le Kernec University of Glasgow
Affiliation
Microwave Sensing, Signals & Systems
More Info
expand_more

Published Date

2021

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Affiliation

Microwave Sensing, Signals & Systems

Abstract

Human Activity Classification with radar has made significant progress in the past few years. In this article, we propose a cyclostationarity-based approach in this field of application. Feature extraction, selection, and activity classification as it detects micro-Doppler is made starting from complex-valued cyclostationary statistical functions of the reflected radar signal. The human activity can be recognized with up to 92.6% with the real part, 95.4% with the imaginary part and 95.4% by the combination of real and imaginary part.

Files

Radar-based_Human_Activity_Cla... (pdf)
(pdf | 4.11 Mb)
License info not available

Download not available