TY - GEN
T1 - Mitigation of UWB Radar Self-Motion for mm-Scale Vibration Detection
AU - Ma, Xujun
AU - Wang, Pei
AU - Chen, Luan
AU - Zhang, Fusang
AU - Zhang, Daqing
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022/1/1
Y1 - 2022/1/1
N2 - To reliably detect a target's mm-scale vibration with a handheld ultra-wideband (UWB) radar system, it is essential to mitigate radar self-motion (RSM) caused by unavoidable hand shaking. In this paper, to further mitigate the effect of stationary objects surrounding the target in real deployment environment, a more practical RSM signal model is proposed. Affected by adjacent objects and RSM, traditional variance-based target positioning method becomes unreliable and the quality of target signal degrades severely as the target's position is often estimated inaccurately. To tackle this problem, an extended bin selection strategy is adopted by considering multiple range bins around the target and independent component analysis (ICA) is leveraged to separate target motion and RSM. Experiments are conducted to verify the proposed technique, and a mm-scale mechanical vibration is reliably detected from 0.5-2m away with the handheld UWB radar system, achieving a median frequency estimation error rate lower than 3.7% under different adjacent environments.
AB - To reliably detect a target's mm-scale vibration with a handheld ultra-wideband (UWB) radar system, it is essential to mitigate radar self-motion (RSM) caused by unavoidable hand shaking. In this paper, to further mitigate the effect of stationary objects surrounding the target in real deployment environment, a more practical RSM signal model is proposed. Affected by adjacent objects and RSM, traditional variance-based target positioning method becomes unreliable and the quality of target signal degrades severely as the target's position is often estimated inaccurately. To tackle this problem, an extended bin selection strategy is adopted by considering multiple range bins around the target and independent component analysis (ICA) is leveraged to separate target motion and RSM. Experiments are conducted to verify the proposed technique, and a mm-scale mechanical vibration is reliably detected from 0.5-2m away with the handheld UWB radar system, achieving a median frequency estimation error rate lower than 3.7% under different adjacent environments.
KW - Adjacent objects
KW - handheld UWB radar
KW - independent component analysis
KW - radar self-motion (RSM)
U2 - 10.1109/IWS55252.2022.9978061
DO - 10.1109/IWS55252.2022.9978061
M3 - Conference contribution
AN - SCOPUS:85146252447
T3 - 2022 IEEE MTT-S International Wireless Symposium, IWS 2022 - Proceedings
BT - 2022 IEEE MTT-S International Wireless Symposium, IWS 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE MTT-S International Wireless Symposium, IWS 2022
Y2 - 12 August 2022 through 15 August 2022
ER -