Radar-based Human Activity Classification with Cyclostationarity

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Radar-based Human Activity Classification with Cyclostationarity

Conference Paper (2021)

Author(s)

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 (TU Delft - Microwave Sensing, Signals & Systems)

Julien Le Kernec (University of Glasgow)

Microwave Sensing, Signals & Systems

DOI related publication

https://doi.org/10.1109/Radar53847.2021.10027946

Assisted living Human activity classification Cyclostationary Microwave radar

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https://resolver.tudelft.nl/uuid:13d37099-30ba-4305-b366-b102ffb08eb8

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Publication Year

2021

Language

English

Microwave Sensing, Signals & Systems

Pages (from-to)

1483-1487

ISBN (electronic)

9781665498142

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.

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