Multi-Person Localization via RF Body Reflections

By Fadel M. Adib, Zachary Kabelac, Dina Katabi. Symposium on Networked Systems Design and Implementation, 2015

394 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e01b85c99482467b697401bb4222b71e472f8cc0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Kun Qian
2. Yi Zhang
3. Zheng Yang
4. Yue Zheng
5. Yaxiong Xie
6. Xuyu Wang
7. Chenshu Wu
8. Fadel M. Adib

Citations in the corpus

• Widar3.0: Zero-Effort Cross-Domain Gesture Recognition With Wi-Fi (2021, methodology): “WiTrack [21], [22] develops FMCW radar with wide bandwidth to accurately estimate ToFs of reflected signals.”
• Capturing the human figure through a wall (2015, background): “…them to carry a wireless transmitter, e.g., [Adib et al. 2014; Joshi et al. 2015; Adib and Katabi 2013; Wang et al. 2014b; Pu et al. 2013; Abdelnasser et al. 2015; Chetty et al. 2012; Wilson and Patwari 2011; Youssef et al. 2007; Nan-nuru et al. 2013; Seifeldin et al. 2013; Adib et al. 2015].”
• A Survey on Wireless Indoor Localization from the Device Perspective (2016, background): “Existing approaches for multiperson localization [Xu et al. 2013; Adib et al. 2015] mainly adopt a successive cancelation scheme to separate the impact of each person, yet require either a network of multiple links [Xu et al.”
• Wireless Sensing for Human Activity: A Survey (2020, background): “…[67]–[71], [84]–[91] FMCW-based Frequency shift associated with human body depth Fine-grained Yes [28], [42]–[44], [55]–[57] [29], [30], [45], [98], [99] Doppler Shift-based Frequency shift associated with human body moving speed Fine-grained Yes [28]–[30], [45], [58]–[66], [92]–[95] WiFi device”
• Widar2.0: Passive Human Tracking with a Single Wi-Fi Link (2018, methodology): “Various hardware [2–4 , 11] are manufactured manufactured to Since dedicated hardware are difficult to be generalized, re-searchesareshiftedtoubiquitousCOTSRFdevices,suchasRFID [26, 27, 33, 42], millimetre wave [35, 45] and Wi-Fi [21, 32].”
• mD-Track: Leveraging Multi-Dimensionality for Passive Indoor Wi-Fi Tracking (2018, background): “el signals from static objects and then estimate the AoA of the signal reflected off the human, which can track the direction of human’s movement, but no location information can be obtained. WiTrack [3, 4] and other systems [8, 16, 23, 37, 58, 59] use dedicated hardware with more than 1 GHz bandwid”
• WiFall: Device-free fall detection by wireless networks (2017, background): “0 [16] achieves 3D motion tracking of multiple targets.”
• Widar: Decimeter-Level Passive Tracking via Velocity Monitoring with Commodity Wi-Fi (2017, background): “Isolating certain reflections can be done in either time domain [9] or frequency domain [1, 2].”
• Zero-Effort Cross-Domain Gesture Recognition with Wi-Fi (2019, background): “WiTrack [3, 4] develops FMCW radar with wide bandwidth to accurately estimate ToFs of reflected signals.”