A Comparative Study on Human Movement Classification Using Wi-Fi Based Passive Forward Scattering Radar

• Published in: TEM Journal
• Main Author: Nasarudin M.N.F.; Razali H.; Ismail N.N.; Zakaria N.A.Z.; Alnaeb A.; Ali M.S.A.M.; Rashid N.E.A.
• Format: Article
• Language: English
• Published: UIKTEN - Association for Information Communication Technology Education and Science 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171459461&doi=10.18421%2fTEM123-13&partnerID=40&md5=8f71ff234a9a21112b9b6e1f07770ebc
• ISSN: 22178309
• DOI: 10.18421/TEM123-13

Forward scattering radar has been widely used to classify human movements. To reduce concern of prolonged radiation exposure, Wi-Fi based passive scattering radar with bistatic topology is proposed. The movements include walking, bending, sitting, and kneeling. The enveloping algorithm applied to Wi-Fi based passive forward scattering radar signals has produced a comparable pattern to the ones from the active configuration. The features extracted from the frequency spectrum are also similar for both radar topologies. These led to comparable performance when classifying using artificial neural network. Hence, Wi-Fi can effectively reduce the cost of radar sensors. © 2023 Muhammad Nazrin Farhan Nasarudin et al; published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License.