TY - GEN
T1 - Static Human Detection in Clutter Environment
AU - Xing, Zhixuan
AU - Chen, Penghui
AU - Bai, Yujing
AU - Song, Jinhao
AU - Wang, Jun
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Indoor human detection using radars is popular as it provides continuous surveillance and detection capabilities. However, the technology also poses challenges such as a higher cost and false alarms caused by non-target signals. In order to tackle it, a novel method is proposed which can removing static noises, time-variant signals and ghost targets comprehensively. Through the experiments and analysis, it can be found the method performs well when a human stands still in a room near a houseplant.
AB - Indoor human detection using radars is popular as it provides continuous surveillance and detection capabilities. However, the technology also poses challenges such as a higher cost and false alarms caused by non-target signals. In order to tackle it, a novel method is proposed which can removing static noises, time-variant signals and ghost targets comprehensively. Through the experiments and analysis, it can be found the method performs well when a human stands still in a room near a houseplant.
KW - indoor human detection
KW - multipath removal
KW - non-target signal suppression
UR - https://www.scopus.com/pages/publications/85191177869
U2 - 10.1109/EEBDA60612.2024.10485862
DO - 10.1109/EEBDA60612.2024.10485862
M3 - 会议稿件
AN - SCOPUS:85191177869
T3 - 2024 IEEE 3rd International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024
SP - 43
EP - 46
BT - 2024 IEEE 3rd International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2024
Y2 - 27 February 2024 through 29 February 2024
ER -