Radar-based Human Activity Classification with Cyclostationarity
Year: 2021
Type: conference-paper
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.
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3211249280