Dude, where's my card?: RFID positioning that works with multipath and non-line of sight

By Jue Wang, Dina Katabi. Conference on Applications, Technologies, Architectures, and Protocols for Computer Communication, 2013

582 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Media Technology, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/a4cec69ca1ef9f6a63a285a8c499e14c93a238f5

How researchers see this paper

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

In Electrical and Electronic Engineering

1. Shiwen Mao
2. Dina Katabi
3. Yunhao Liu
4. Xuyu Wang
5. Kyle Jamieson
6. Jie Xiong
7. Lingjun Gao
8. Zimu Zhou

In Media Technology

1. Jie Xiong
2. Fadel M. Adib
3. Zachary Kabelac
4. Kin Kwong Leung
5. Faheem Zafari
6. Athanasios Gkelias
7. Zimu Zhou
8. Lionel Ming-shuan Ni

In Ocean Engineering

1. Shiwen Mao
2. Xuyu Wang
3. Lingjun Gao
4. Zimu Zhou
5. Lionel Ming-shuan Ni
6. Jie Xiong
7. Yunhao Liu
8. Kyle Jamieson

Citations in the corpus

• SpotFi: Decimeter Level Localization Using WiFi (2015, methodology): “Other approaches: For completeness, we refer to localization systems that deploy other modalities like RFIDs [53, 54, 55], ultrawideband [56], ultrasound [57, 58, 59, 60, 61], IR [62, 63, 64], visible light [65, 66] or beacons like the ones Apple recently introduced [67].”
• CSI-Based Fingerprinting for Indoor Localization: A Deep Learning Approach (2016, methodology): “909 On the other hand, some systems, such as LTEye [45], 910 Ubicarse [46], Wi-Vi [47], and PinIt [48], use synthetic aperture 911 radar (SAR) to mimic an antenna array to improve the resolu- 912 tion of angles.”
• Multi-Person Localization via RF Body Reflections (2015, background): “As with traditional device-based localization, the most difficult challenge in indoor environments is the multipath effect [34, 17].”
• Tagoram: real-time tracking of mobile RFID tags to high precision using COTS devices (2014, methodology): “PinIt: PinIt [6] uses synthetic aperture radar (SAR) created via antenna motion to extract the multipath profiles for each tag, and leverages the reference tags to locate the target tag as same way as RSS based methods.”
• Phaser: enabling phased array signal processing on commodity WiFi access points (2014, background): “Recent examples include systems that localize RFID tags [27] and WiFi devices [22, 30], enhance WiFi security [31], and passive radar systems that pinpoint human movements [1, 2, 17].”
• A Survey on Wireless Indoor Localization from the Device Perspective (2016, methodology): “…technique and achieved a mean accuracy of 12.8cm. MIMO techniques further pushed RFID-based localization to centimeter-level accuracy using Synthetic Aperture Radar (SAR) [Wang and Katabi 2013], Inverse Synthetic Aperture Radar (ISAR) [Scherhaufl et al. 2014], and hologram [Yang et al. 2014].”
• A Survey of Indoor Localization Systems and Technologies (2017, methodology): “While a median accuracy of 11 cm is attained, PinIt is not widely deployable due to the absence of RFID on majority of the user devices.”
• LiFS: low human-effort, device-free localization with fine-grained subcarrier information (2016, methodology): “[33], we use the dynamic time warping (DTW) distance [24] to calculate the dissimilarities of two CSI measurements when a target is at different locations.”
• Accurate indoor localization with zero start-up cost (2014, background): “Ubicarse builds on past work in Synthetic Aperture Radar (SAR) that leverage precise mechanically controlled antenna movements or advanced motion sensing equipment for radar imaging [9] and RFID localization [33, 32].”
• Dynamic-MUSIC: accurate device-free indoor localization (2016, methodology): “Different technologies have been employed for indoor localization, such as camera [3, 4], RF [2, 33, 36, 37, 50], infrared [8, 13], Ultra-wideband (UWB) [9], sound [14, 41], and recently visible light [15, 20], etc.”
• We Can Hear You with Wi-Fi! (2014, background): “[45] to classify the same word spoken at different speeds into the same group.”
• Caraoke: An E-Toll Transponder Network for Smart Cities (2015, result): “Our work is also related to past work on RFID localization and RF-based positioning [60, 29, 59, 63, 26].”
• 3D Tracking via Body Radio Reflections (2014, methodology): “These systems localize a wireless device using RSSI [11, 22], fine-grained-OFDM channel information [25], antenna arrays [31, 18], or RFID backscatter [28, 27].”