@inproceedings{13d3709930ba4305b366b102ffb08eb8,
title = "Radar-based Human Activity Classification with Cyclostationarity",
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.",
keywords = "assisted living, cyclostationary, human activity classification, microwave radar",
author = "Yaxin Du and Jipeng Li and Zhouyixian Li and Ran Yu and Antonio Napolitano and Francesco Fioranelli and \{Le Kernec\}, Julien",
year = "2021",
doi = "10.1109/Radar53847.2021.10027946",
language = "English",
series = "Proceedings of the IEEE Radar Conference",
publisher = "IEEE",
pages = "1483--1487",
booktitle = "2021 CIE International Conference on Radar, Radar 2021",
address = "United States",
note = "2021 CIE International Conference on Radar, Radar 2021 ; Conference date: 15-12-2021 Through 19-12-2021",
}