TY - JOUR
T1 - Size Matters
T2 - Characterizing the Effect of Target Size on Wi-Fi Sensing Based on the Fresnel Zone Model
AU - Wang, Zhu
AU - Geng, Chendi
AU - Sun, Zhuo
AU - Chen, Zhen
AU - Liu, Sicong
AU - Guo, Bin
AU - Yu, Zhiwen
N1 - Publisher Copyright:
© 2024 ACM.
PY - 2024/11/21
Y1 - 2024/11/21
N2 - The model-based Wi-Fi sensing approach has shown advantages on facilitating the development of more robust sensing systems, due to its capability of revealing the physical and mathematical sensing mechanisms without the requirement of a large set of training data. Existing models usually treat the sensing target as a particle and characterize the propagation of Wi-Fi signals accordingly, i.e., the effect of target size is ignored. However, in most real-world scenarios, the sensing targets are non-particle and different targets usually have different sizes. Considering that the size difference may have a significant impact on the sensing performance, it is necessary to develop a size-aware model to enrich the Wi-Fi sensing theory. To fill this gap, we propose a non-particle target oriented Wi-Fi sensing model, aiming to describe the relationship between the Wi-Fi signal and the target size. Specifically, by extending the classical particle target oriented Wi-Fi Fresnel zone model, we characterize and quantify the reflected signals from different parts of the non-particle target in a more fine-grained manner. We find the amplitude of the reflected Wi-Fi signals increases and decreases periodically along with the changing of the target size, which is called as the oscillation phenomenon. To validate the proposed model, we implement two sensing applications with a pair of transceivers, including a respiration detection system and a target size measurement system. Extensive experiments demonstrate the correctness and the usefulness of the proposed size-aware model. To the best of our knowledge, this is the first theoretical model that reveals the effect of target size on Wi-Fi sensing.
AB - The model-based Wi-Fi sensing approach has shown advantages on facilitating the development of more robust sensing systems, due to its capability of revealing the physical and mathematical sensing mechanisms without the requirement of a large set of training data. Existing models usually treat the sensing target as a particle and characterize the propagation of Wi-Fi signals accordingly, i.e., the effect of target size is ignored. However, in most real-world scenarios, the sensing targets are non-particle and different targets usually have different sizes. Considering that the size difference may have a significant impact on the sensing performance, it is necessary to develop a size-aware model to enrich the Wi-Fi sensing theory. To fill this gap, we propose a non-particle target oriented Wi-Fi sensing model, aiming to describe the relationship between the Wi-Fi signal and the target size. Specifically, by extending the classical particle target oriented Wi-Fi Fresnel zone model, we characterize and quantify the reflected signals from different parts of the non-particle target in a more fine-grained manner. We find the amplitude of the reflected Wi-Fi signals increases and decreases periodically along with the changing of the target size, which is called as the oscillation phenomenon. To validate the proposed model, we implement two sensing applications with a pair of transceivers, including a respiration detection system and a target size measurement system. Extensive experiments demonstrate the correctness and the usefulness of the proposed size-aware model. To the best of our knowledge, this is the first theoretical model that reveals the effect of target size on Wi-Fi sensing.
KW - Fresnel Zone
KW - Respiration Detection
KW - Size-Aware Model
KW - Target Size
KW - Wi-Fi CSI
UR - http://www.scopus.com/inward/record.url?scp=85210299409&partnerID=8YFLogxK
U2 - 10.1145/3699726
DO - 10.1145/3699726
M3 - 文章
AN - SCOPUS:85210299409
SN - 2474-9567
VL - 8
JO - Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
JF - Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
IS - 4
M1 - 209
ER -