Widar2.0: Passive Human Tracking with a Single Wi-Fi Link

By Kun Qian, Chenshu Wu, Yi Zhang, Guidong Zhang, Zheng Yang, Yunhao Liu. ACM SIGMOBILE International Conference on Mobile Systems, Applications, and Services, 2018

490 citations recorded by the source corpus.

This paper presents Widar2.0, the first WiFi-based system that enables passive human localization and tracking using a single link on commodity off-the-shelf devices. Previous works based on either specialized or commercial hardware all require multiple links, preventing their wide adoption in scenarios like homes where typically only one single AP is installed. The key insight underlying Widar2.0 to circumvent the use of multiple links is to leverage multi-dimensional signal parameters from one single link. To this end, we build a unified model accounting for Angle-of-Arrival, Time-of-Flight, and Doppler shifts together and devise an efficient algorithm for their joint estimation. We then design a pipeline to translate the erroneous raw parameters into precise locations, which first finds parameters corresponding to the reflections of interests, then refines range estimates, and ultimately outputs target locations. Our implementation and evaluation on commodity WiFi devices demonstrate that Widar2.0 achieves better or comparable performance to state-of-the-art localization systems, which either use specialized hardwares or require 2 to 40 Wi-Fi links.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/957e4c03e7846a1f8670b250f5f9661c91dfcb75

How researchers see this paper

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

In Artificial Intelligence

1. Mo Li
2. Kun Qian
3. Kyle Jamieson
4. Yunhao Liu
5. Guidong Zhang
6. Yue Zheng
7. Yi Zhang
8. Chenshu Wu

In Electrical and Electronic Engineering

1. Kun Qian
2. Zheng Yang
3. Kyle Jamieson
4. Chenshu Wu
5. Yunhao Liu
6. Jie Xiong
7. Guidong Zhang
8. Yi Zhang

Citations in the corpus

• Widar3.0: Zero-Effort Cross-Domain Gesture Recognition With Wi-Fi (2021, methodology): “0 [18] track coarse human motion status, e.g., torso location and velocity, by extracting the features from the dominant reflected signal off body torso.”
• Zero-Effort Cross-Domain Gesture Recognition with Wi-Fi (2019, background): “Besides, when the person is close to the Wi-Fi link, only signals with one time reflection have prominent magnitudes [33] as Figure 3 shows.”
• mD-Track: Leveraging Multi-Dimensionality for Passive Indoor Wi-Fi Tracking (2018, background): “D-Track not only provides motion related information, i.e., Doppler, but also estimated location related information, i.e., AoA, AoD and ToF, for every resolvable multipath. While some recent systems [18, 19, 27, 35, 49] consider the use of multiple parameters for object tracking, their systems are ”
• An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing (2021, unknown): “There have been a limited number of works that address this problem in passive WiFi sensing [42]–[44], based on the cross-antenna cross-correlation (CACC) method.”
• Enabling Joint Communication and Radar Sensing in Mobile Networks—A Survey (2020, methodology): “In [203], CACC is used to obtain estimates for ranges and velocities of targets.”