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iSense: Enabling Radar Sensing Under Mutual Device Interference

delete2024-11-01
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PRE
AI
S
Shuai Yang
D
Dongheng Zhang
Y
Yadong Li
Y
Yang Hu
孙
孙启彬 (Qibin Sun)
Y
Yan Chen *
DOI:10.1109/TMC.2024.3379570delete
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摘要

摘要

En 中文
Millimeter-wave (mmWave) radar has been widely used in wireless sensing due to its non-contact nature, privacy preservation, and immunity to adverse lighting conditions. However, with more and more mmWave radars working in the same frequency band, mutual device interference among them is inevitable and has become a serious problem. The device interference reduces the signal-to-interference-plus-noise ratio (SINR) and significantly degrades the detection performance. Existing works mainly focus on the vital sign monitoring in different practical scenarios (e.g., device movement, human movement, multi-person interference, and in-car scenario), and the vital sign monitoring in the presence of mutual device interference is still not well resolved. In this paper, we propose a novel interference mitigation framework, iSense, to enable radar vital sign sensing under device interference. By exploiting one-way propagation characteristic of device interference, iSense can effectively detect and suppress the interference. We evaluate iSense under a variety of complex device interference scenarios, including different distances, angles, and numbers of aggressor radars, as well as the impact of different environments. Experimental results show that the accuracy of respiration and heartbeat estimation of iSense can reach over 99.2% and 98.6%, indicating that iSense takes an important step towards the practical development of radar sensing.
Keyword:
radar sensing
Mutual device interference
spectral estimation
vital sign monitoring
vital sign monitoring
spectral estimation
vital sign monitoring

期刊

IEEE Transactions on Mobile Computing 封面图
IEEE Transactions on Mobile Computing
IF:
9.2
论文数:
5.9K
被引数:
1.8W

机构

U
university of science & technology of china, cas
学者数:
3.2W
论文数: 2.7W
被引数: 74
C
chinese academy of sciences
学者数:
56.7W
论文数: 45.0W
被引数: 704
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