research-article

3D-OmniTrack: 3D tracking with COTS RFID systems

Authors:

Chengkun Jiang,

Yunhao LiuAuthors Info & Claims

IPSN '19: Proceedings of the 18th International Conference on Information Processing in Sensor Networks

Pages 25 - 36

https://doi.org/10.1145/3302506.3310386

Published: 16 April 2019 Publication History

Abstract

RFID tracking has attracted significant interest from both academia and industry due to its low cost and ease of deployment. Previous works focus more on tracking in 2D space or separately consider tracking of the location and the orientation. They especially struggle in 3D situations due to the increase in the degree of freedom and the limited information conveyed by the RFID tags. In this paper, we propose 3D-OmniTrack, an approach that can accurately track the 3D location and orientation of an object. We introduce a polarization-sensitive phase model in an RFID system, which takes into consideration both the distance and the 3D posture of an object. Based on this model, we design an algorithm to accurately track the object in 3D space. We conduct real-world experiments and present results that show 3D-OmniTrack can achieve centimeter-level location accuracy with the average orientation error of 5°. 3D-OmniTrack has significant advantages in both the accuracy and the efficiency, compared with state-of-the-art approaches.

References

[1]

S. S. Blackman. Multiple hypothesis tracking for multiple target tracking. IEEE Aerospace and Electronic Systems Magazine, 19(1):5--18, 2004.

[2]

C. Bo, T. Jung, X. Mao, X.-Y. Li, and Y. Wang. Smartloc: Sensing landmarks silently for smartphone-based metropolitan localization. EURASIP Journal on Wireless Communications and Networking, 2016(1):111, 2016.

[3]

J. L. Brchan, L. Zhao, J. Wu, R. E. Williams, and L. C. Pérez. A real-time rfid localization experiment using propagation models. In Procs. of IEEE RFID, 2012.

[4]

N. Brouwers, M. Zuniga, and K. Langendoen. Incremental wi-fi scanning for energy-efficient localization. In Procs. of IEEE PerCom, 2014.

[5]

Y. Bu, L. Xie, J. Liu, B. He, Y. Gong, and S. Lu. 3-dimensional reconstruction on tagged packages via rfid systems. In Procs. of IEEE SECON, 2017.

[6]

K. DorfmÃijller. An Optical Tracking System for VR/AR-Applications. Springer Vienna, 1999.

[7]

J. Hightower, R. Want, and G. Borriello. Spoton: An indoor 3d location sensing technology based on rf signal strength. 2000.

[8]

C. Jiang, Y. He, X. Zheng, and Y. Liu. Orientation-aware rfid tracking with centimeter-level accuracy. In Procs. of ACM/IEEE IPSN, 2018.

Digital Library

[9]

X. Li, Y. Zhang, and M. G. Amin. Multifrequency-based range estimation of rfid tags. In Procs. of IEEE RFID, 2009.

[10]

T. Liu, Y. Liu, L. Yang, Y. Guo, and C. Wang. Backpos: High accuracy backscatter positioning system. IEEE Transactions on Mobile Computing, 15(3):586--598, 2016.

Digital Library

[11]

Y. Ma, N. Selby, and F. Adib. Minding the billions: Ultra-wideband localization for deployed rfid tags. In Procs. of ACM MobiCom, 2017.

Digital Library

[12]

H. Nam and B. Han. Learning multi-domain convolutional neural networks for visual tracking. In Procs. of IEEE CVPR, 2016.

[13]

L. M. Ni, Y. Liu, Y. C. Lau, and A. P. Patil. Landmarc: indoor location sensing using active rfid. Wireless networks, 10(6):701--710, 2004.

Digital Library

[14]

S. Satyavolu, G. Bruder, P. Willemsen, and F. Steinicke. Analysis of ir-based virtual reality tracking using multiple kinects. In Virtual Reality Short Papers and Posters, pages 149--150, 2012.

Digital Library

[15]

L. Shangguan and K. Jamieson. The design and implementation of a mobile rfid tag sorting robot. In Procs. of USENIX NSDI, 2016.

Digital Library

[16]

L. Shangguan, Z. Yang, A. X. Liu, Z. Zhou, and Y. Liu. Stpp: Spatial-temporal phase profiling-based method for relative rfid tag localization. IEEE/ACM Transactions on Networking, 25(1):596--609, 2017.

Digital Library

[17]

S. Shen, H. Wang, and R. Roy Choudhury. I am a smartwatch and i can track my user's arm. In In Procs. of ACM MobiSys, 2016.

Digital Library

[18]

Y. Shen, W. Hu, M. Yang, J. Liu, B. Wei, S. Lucey, and C. T. Chou. Real-time and robust compressive background subtraction for embedded camera networks. IEEE Transactions on Mobile Computing, 15(2):406--418, 2016.

Digital Library

[19]

J. Wang, F. Adib, R. Knepper, D. Katabi, and D. Rus. Rf-compass: Robot object manipulation using rfids. In Procs. of ACM MobiCom, 2013.

Digital Library

[20]

W. Wang, A. X. Liu, and K. Sun. Device-free gesture tracking using acoustic signals. In Procs. of ACM MobiCom, 2016.

Digital Library

[21]

T. Wei and X. Zhang. Gyro in the air: tracking 3d orientation of batteryless internet-of-things. In Procs. of ACM MobiCom, 2016.

Digital Library

[22]

Y. Wen, X. Tian, X. Wang, and S. Lu. Fundamental limits of rss fingerprinting based indoor localization. In Procs. of IEEE INFOCOM, 2015.

[23]

N. Wojke, A. Bewley, and D. Paulus. Simple online and realtime tracking with a deep association metric. In Procs. of IEEE ICIP, pages 3645--3649, 2017.

[24]

C. Wu, Z. Yang, Y. Xu, Y. Zhao, and Y. Liu. Human mobility enhances global positioning accuracy for mobile phone localization. IEEE Transactions on Parallel and Distributed Systems, 26(1):131--141, 2015.

[25]

F. Xiao, Z. Wang, N. Ye, R. Wang, and X.-Y. Li. One more tag enables fine-grained rfid localization and tracking. IEEE/ACM Transactions on Networking, 26(1):161--174, 2018.

Digital Library

[26]

Z. Xiao, H. Wen, A. Markham, and N. Trigoni. Lightweight map matching for indoor localisation using conditional random fields. In Procs. of ACM/IEEE IPSN, 2014.

Digital Library

[27]

C. Xu, B. Firner, Y. Zhang, R. Howard, J. Li, and X. Lin. Improving rf-based device-free passive localization in cluttered indoor environments through probabilistic classification methods. In Procs. of ACM/IEEE IPSN, 2012.

Digital Library

[28]

L. Yang, Y. Chen, X.-Y. Li, C. Xiao, M. Li, and Y. Liu. Tagoram: Real-time tracking of mobile rfid tags to high precision using cots devices. In Procs. of ACM MobiCom, 2014.

Digital Library

[29]

L. Yao, Q. Z. Sheng, X. Li, T. Gu, M. Tan, X. Wang, S. Wang, and W. Ruan. Compressive representation for device-free activity recognition with passive rfid signal strength. IEEE Transactions on Mobile Computing, 17(2):293--306, 2018.

Digital Library

[30]

Y. Yin, L. Xie, Y. Fan, and S. Lu. Tracking human motions in photographing: A context-aware energy-saving scheme for smart phones. ACM Transactions on Sensor Networks, 13(4):29, 2017.

Digital Library

[31]

C. Zhang, J. Tabor, J. Zhang, and X. Zhang. Extending mobile interaction through near-field visible light sensing. In Procs. of ACM MobiCom, 2015.

Digital Library

[32]

Y. Zhao, Y. Liu, T. Yu, T. He, and C. Qian. Fredi: Robust rss-based ranging with multipath effect and radio interference. Computer Networks, 147:49--63, 2018.

Cited By

Wang HLi SZhou YWang YPan RPang S(2024)Tag-Array-Based UHF Passive RFID Tag Attitude Identification of Tracking MethodsSensors10.3390/s2419630524:19(6305)Online publication date: 29-Sep-2024
https://doi.org/10.3390/s24196305
Zheng JChen THe JWang ZGao B(2024)Review on Security Range Perception Methods and Path-Planning Techniques for Substation Mobile RobotsEnergies10.3390/en1716410617:16(4106)Online publication date: 18-Aug-2024
https://doi.org/10.3390/en17164106
Mao YYan YWang SLi X(2024)Stabilizing Dynamic Backscatter for Swift and Accurate Object TrackingACM Transactions on Sensor Networks10.1145/368747920:5(1-18)Online publication date: 12-Aug-2024
https://dl.acm.org/doi/10.1145/3687479
Show More Cited By

Index Terms

3D-OmniTrack: 3D tracking with COTS RFID systems
1. Computer systems organization
  1. Embedded and cyber-physical systems
  2. Real-time systems
2. Hardware
  1. Communication hardware, interfaces and storage
    1. Sensor applications and deployments

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Published In

cover image ACM Conferences

IPSN '19: Proceedings of the 18th International Conference on Information Processing in Sensor Networks

April 2019

365 pages

ISBN:9781450362849

DOI:10.1145/3302506

General Chair:
Rasit Eskicioglu
University of Manitoba, Canada
,
Program Chairs:
Luca Mottola
Politecnico di Milano, Italy
,
Bodhi Priyantha
Microsoft Research

Copyright © 2019 ACM.

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SIGBED: ACM Special Interest Group on Embedded Systems

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New York, NY, United States

Publication History

Published: 16 April 2019

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Funding Sources

National Natural Science Foundation of China
National Key R&D Program of China

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IPSN '19

Sponsor:

SIGBED

IPSN '19: The 18th International Conference on Information Processing in Sensor Networks

April 16 - 18, 2019

Quebec, Montreal, Canada

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IPSN '19 Paper Acceptance Rate 25 of 91 submissions, 27%;

Overall Acceptance Rate 143 of 593 submissions, 24%

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Cited By

Wang HLi SZhou YWang YPan RPang S(2024)Tag-Array-Based UHF Passive RFID Tag Attitude Identification of Tracking MethodsSensors10.3390/s2419630524:19(6305)Online publication date: 29-Sep-2024
https://doi.org/10.3390/s24196305
Zheng JChen THe JWang ZGao B(2024)Review on Security Range Perception Methods and Path-Planning Techniques for Substation Mobile RobotsEnergies10.3390/en1716410617:16(4106)Online publication date: 18-Aug-2024
https://doi.org/10.3390/en17164106
Mao YYan YWang SLi X(2024)Stabilizing Dynamic Backscatter for Swift and Accurate Object TrackingACM Transactions on Sensor Networks10.1145/368747920:5(1-18)Online publication date: 12-Aug-2024
https://dl.acm.org/doi/10.1145/3687479
Cao YDhekne AAmmar MOkoshi TKo JLiKamWa R(2024)UTrack3D: 3D Tracking Using Ultra-wideband (UWB) RadiosProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661881(345-358)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3643832.3661881
Xie MJin MZhu FZhang YTian XWang XZhou CGanesan DShi W(2024)Enabling High-rate Backscatter Sensing at ScaleProceedings of the 30th Annual International Conference on Mobile Computing and Networking10.1145/3636534.3649351(124-138)Online publication date: 29-May-2024
https://dl.acm.org/doi/10.1145/3636534.3649351
Bai YShahid ITakawale HRoy N(2024)ScribeProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314117:4(1-31)Online publication date: 12-Jan-2024
https://dl.acm.org/doi/10.1145/3631411
Zhao CLi ZDing HWang GXi WZhao J(2024)Enabling Multi-Frequency and Wider-Band RFID Sensing Using COTS DeviceIEEE/ACM Transactions on Networking10.1109/TNET.2024.339497432:4(3591-3605)Online publication date: Aug-2024
https://doi.org/10.1109/TNET.2024.3394974
Zhang YLi YChen BLi EZheng KChi KZhu Y(2024)Design of an RFID-Based Self-Jamming Identification and Sensing PlatformIEEE Transactions on Mobile Computing10.1109/TMC.2023.3280942(1-15)Online publication date: 2024
https://doi.org/10.1109/TMC.2023.3280942
Liu HMeng ZXu JLi CLi ZGao NZhang Z(2024)Simultaneous Detection of the Orientation and Position of Moving Objects With Simple RFID Array for Industrial IoT ApplicationsIEEE Internet of Things Journal10.1109/JIOT.2024.340319511:17(28752-28764)Online publication date: 1-Sep-2024
https://doi.org/10.1109/JIOT.2024.3403195
Zhu YZhang Q(2024)LoPrint: Mobile Authentication of RFID-Tagged Items Using COTS Orthogonal AntennasIEEE INFOCOM 2024 - IEEE Conference on Computer Communications10.1109/INFOCOM52122.2024.10621362(1551-1560)Online publication date: 20-May-2024
https://doi.org/10.1109/INFOCOM52122.2024.10621362
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