ArrayTrack: A Fine-Grained Indoor Location System

By Jie Xiong, Kyle Jamieson. Symposium on Networked Systems Design and Implementation, 2011

1,017 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/670d3c3b3c73663af26962cedb3f7f0a9c6f40ca

How researchers see this paper

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

1. Xuyu Wang
2. Kun Qian
3. Yaxiong Xie
4. Wen Wang
5. Yi Zhang
6. Zheng Yang
7. Jie Xiong
8. Chenshu Wu

Citations in the corpus

• See through walls with WiFi! (2013, methodology): “The basic approach for processing such signals relies on the smoothed MUSIC algorithm [31, 39].”
• Magicol: Indoor Localization Using Pervasive Magnetic Field and Opportunistic WiFi Sensing (2015, background): “WiFi [1]–[4], cellular [5]–[7], or even FM [8], [9] based approaches have shown great promise but may not be as effective when the signals are”
• Accurate indoor localization with zero start-up cost (2014, background): “This is because past work that provides accurate RF-localization falls in one of two categories: 1) It either requires the deployment of new infrastructure (specialized access points [15], antenna arrays [37], acoustic beacons [19], etc.”
• Recent Advances in Wireless Indoor Localization Techniques and System (2013, background): “Xiong and Jamieson [47] presented ArrayTrack, an indoor location system that uses angle-of-arrival techniques to locate wireless clients indoors in a wireless local area network.”
• Non-Invasive Detection of Moving and Stationary Human With WiFi (2015, unknown): “radios [38] and standard WiFi infrastructure [39].”
• Epsilon: A Visible Light Based Positioning System (2014, methodology): “(1) The deployment of illumination lights is much (over one order of magnitude) denser than that of WiFi access points (APs).”
• RF-based 3D skeletons (2018, background): “Novel algorithms have led to accurate localization within tens of centimeters [19, 34].”
• Caraoke: An E-Toll Transponder Network for Smart Cities (2015, methodology): “It is widely-known that the angle of arrival can be computed as [60]:”
• Through-Wall Human Pose Estimation Using Radio Signals (2018, background): “For example, one can track a person using the WiFi signal from their cellphone [44, 24, 40].”
• 3D Tracking via Body Radio Reflections (2014, methodology): “In particular, RF localization using WiFi and other communication devices has reached sub-meter accuracy and demonstrated its ability to deal with occlusions and non-line of sight scenarios [31, 18].”
• Phaser: enabling phased array signal processing on commodity WiFi access points (2014, methodology): “These measure the two-dimensional bearing at which a transmission arrives at the AP [14, 30].”
• Towards 3D human pose construction using wifi (2020, background): “…are conducted to make use of WiFi devices to enable various sensing tasks, including indoor localization and tracking [5, 22, 25, 33, 39, 42, 48–50, 52, 53, 65], walking speed estimation [17, 43], breathing and heartbeats inference [6, 55, 58, 61], human identification [16, 43, 54], human or…”
• WiFi-based indoor positioning (2015, methodology): “The traditional approaches in [10, 15] require a certain number of antennas to overcome the multipath effect.”
• Wireless Sensing for Human Activity: A Survey (2020, methodology): “Xiong and Jamieson [81] propose ArrayTrack, which requires no calibration beforehand to achieve high localization accuracy using RSSI.”
• A Survey of Indoor Localization Systems and Technologies (2017, background): “Angle of Arrival (AoA) based approaches use antennae arrays [22] (at the receiver side) to estimate the angle at which the transmitted signal impinges on the receiver by exploiting and calculating the time difference of arrival at individual elements of the antennae array.”