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Stabilizing Dynamic Backscatter for Swift and Accurate Object Tracking

Published: 20 September 2024 Publication History

Abstract

Accurate and high-speed object movement tracking systems often face significant challenges due to signal instability caused by the object’s movement and rotation. To address these issues, we present STABack, a novel object tracking system using backscatter tags and accelerometer sensors, designed for high-accuracy, high-speed movement tracking. We developed an amplitude stabilization algorithm which uses envelope detection to reduce the impact of high-frequency movement on the signal, and uses dynamic threshold output to lower the BER in backscatter demodulation. Our method reduces the BER by 0.3757 compared to the regular demodulation method, resulting in a final BER of 0.07. Our evaluation of the STABack prototype shows that it achieves a median distance measurement accuracy of 6.45 cm with a standard deviation of 6.95 cm, under the condition of a speed of 120 cm. The attitude angle estimation’s mean error is under 7 degrees. The system’s accuracy in detecting the target object’s trajectory is as high as 99%, and it can still decode with a bit error rate of no more than 0.034 at a speed of 166 cm/s. The power consumption of our system prototype is only 38.54 μW based on our experimental results. Overall, our results demonstrate that STABack can accurately estimate the movement and rotation of target objects in unstable backscatter channels.

References

[1]
Analog. 2023. ADG902 Datasheet and Product Info | Analog Devices. (2023). Retrieved November 08, 2023 from https://www.analog.com/en/products/adg902.html
[2]
Analog. 2023. ADXL362 Datasheet and Product Info | Analog Devices. (2023). Retrieved November 08, 2023 from https://www.analog.com/en/products/adxl362.html
[3]
Apple. 2023. AirTag. (2023). Retrieved April 29, 2023 from https://www.apple.com/airtag/
[4]
R. Bavya and R. Mohanamurali. 2014. Next generation auto theft prevention and tracking system for land vehicles. In Proceedings of the International Conference on Information Communication and Embedded Systems (ICICES2014’14). IEEE, 1–5. DOI:DOI:
[5]
Wan-Jung Chang, Jian-Ping Su, Chia-Hao Hsu, Liang-Bi Chen, Ming-Che Chen, Huang-Chih Chen, and Chiu-Fa Lin. 2019. iCAP: An IoT-based intelligent liquid waste barrels monitoring system. In Proceedings of the 2019 11th Computer Science and Electronic Engineering (CEEC’19). IEEE, 156–159. DOI:DOI:
[6]
Pi-Chun Chen. 1999. A non-line-of-sight error mitigation algorithm in location estimation. In Proceedings of the IEEE Wireless Communications and Networking Conference (Cat. No.99TH8466), WCNC 1999. Vol. 1, IEEE, 316–320. DOI:DOI:
[7]
Hoon Choi, Sanghyun Son, Jamje Kim, and Yunju Baek. 2010. RF-based indoor locating system for NLOS environment. In Proceedings of the 2010 24th IEEE International Conference on Advanced Information Networking and Applications. IEEE, 628–633. DOI:DOI:
[8]
Daniel Mark Dobkin. 2013. The RF in RFID: UHF RFID in Practice (2nd ed.). Elsevier/Newnes, Amsterdam.
[9]
Robert P. Freckleton. 2011. Dealing with collinearity in behavioural and ecological data: Model averaging and the problems of measurement error. Behavioral Ecology and Sociobiology 65, 1 (Jan.2011), 91–101. DOI:DOI:
[10]
F. N. Fritsch and J. Butland. 1984. A method for constructing local monotone piecewise cubic interpolants. SIAM Journal on Scientific and Statistical Computing 5, 2 (1984), 300–304. DOI:DOI:
[11]
Peng Gao, Yipeng Ma, Ke Song, Chao Li, Fei Wang, Liyi Xiao, and Yan Zhang. 2018. High performance visual tracking with circular and structural operators. Knowledge-Based Systems 161 (Dec.2018), 240–253. DOI:DOI:
[12]
Peng Gao, Ruyue Yuan, Fei Wang, Liyi Xiao, Hamido Fujita, and Yan Zhang. 2020. Siamese attentional keypoint network for high performance visual tracking. Knowledge-Based Systems 193 (April2020), 105448. DOI:DOI:
[13]
Peng Gao, Qiquan Zhang, Fei Wang, Liyi Xiao, Hamido Fujita, and Yan Zhang. 2020. Learning reinforced attentional representation for end-to-end visual tracking. Information Sciences 517 (May2020), 52–67. DOI:DOI:
[14]
Peng Gao, Xin-Yue Zhang, Xiao-Li Yang, Feng Gao, Hamido Fujita, and Fei Wang. 2024. Robust visual tracking with extreme point graph-guided annotation: Approach and experiment. Expert Systems with Applications 238 (March2024), 122013. DOI:DOI:
[15]
Alireza Ghasempour. 2019. Internet of Things in smart grid: Architecture, applications, services, key technologies, and challenges. Inventions 4, 1 (March2019), 22. DOI:DOI:
[16]
GS1. 2023. EPC UHF Gen2 Air Interface Protocol | GS1. (2023). Retrieved Feburary 05, 2023 from https://www.gs1.org/standards/rfid/uhf-air-interface-protocol
[17]
Kai Huang, Ruirong Chen, and Wei Gao. 2022. RAScatter: Achieving energy-efficient backscatter readers via AI-assisted power adaptation. In Proceedings of the 2022 IEEE/ACM 7th International Conference on Internet-of-Things Design and Implementation (IoTDI’22). 1–13. DOI:DOI:
[18]
Chengkun Jiang, Yuan He, Songzhen Yang, Junchen Guo, and Yunhao Liu. 2019. 3D-OmniTrack: 3D tracking with COTS RFID systems. In Proceedings of the 2019 18th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN’19). 25–36. DOI:DOI:
[19]
Shi Qiang Liu, Jun Chang Zhang, and Rong Zhu. 2020. A wearable human motion tracking device using micro flow sensor incorporating a micro accelerometer. IEEE Transactions on Biomedical Engineering 67, 4 (April2020), 940–948. DOI:DOI:
[20]
MathWorks. Modified Akima Piecewise Cubic Hermite Interpolation - MATLAB Makima. (n.d.). Retrieved April 30, 2023 from https://www.mathworks.com/help/matlab/ref/makima.html
[21]
MathWorks. 2023. Four-Quadrant Inverse Tangent - MATLAB Atan2. (2023). Retrieved April 30, 2023 from https://www.mathworks.com/help/matlab/ref/atan2.html
[22]
Prachi More and Shriram Markande. 2016. Design and implementation of anti-theft module for ATM machine. In Proceedings of the 2016 International Conference on Inventive Computation Technologies (ICICT’16). Vol. 3, 1–4. DOI:DOI:
[23]
Ryota Ozaki and Yoji Kuroda. 2021. DNN-based self-attitude estimation by learning landscape information. In Proceedings of the 2021 IEEE/SICE International Symposium on System Integration (SII’21). 733–738. DOI:DOI:
[24]
Ryota Ozaki and Yoji Kuroda. 2021. EKF-based real-time self-attitude estimation with camera DNN learning landscape regularities. IEEE Robotics and Automation Letters 6, 2 (April2021), 1737–1744. DOI:DOI:
[25]
D. Durga Prasad. 2016. Design and implementation of FM0/Manchester encoder using VHDL. 5, 4 (April 2016), 6.
[26]
Alessandro Sabato, Christopher Niezrecki, and Giancarlo Fortino. 2017. Wireless MEMS-based accelerometer sensor boards for structural vibration monitoring: A review. IEEE Sensors Journal 17, 2 (Jan.2017), 226–235. DOI:DOI:
[27]
Longfei Shangguan and Kyle Jamieson. 2016. Leveraging electromagnetic polarization in a two-antenna whiteboard in the air. In Proceedings of the 12th International Conference on Emerging Networking EXperiments and Technologies. ACM, Irvine California USA, 443–456. DOI:DOI:
[28]
Pekka Siirtola, Perttu Laurinen, Juha Röning, and Hannu Kinnunen. 2011. Efficient accelerometer-based swimming exercise tracking. In Proceedings of the 2011 IEEE Symposium on Computational Intelligence and Data Mining (CIDM’11). 156–161. DOI:DOI:
[29]
M. Taguchi and H. Mizuno. 2006. Analysis of dead zone of RFID system. In Proceedings of the 2006 IEEE Antennas and Propagation Society International Symposium. IEEE, 4759–4762. DOI:DOI:
[31]
TI. 2023. MSP430FR5969 Data Sheet, Product Information and Support | TI.Com. (2023). Retrieved April 30, 2023 from https://www.ti.com/product/MSP430FR5969?keyMatch=MSP430FR5969
[32]
Sebastian Trimpe and Raffaello D’Andrea. 2012. The balancing cube: A dynamic sculpture as test bed for distributed estimation and control. IEEE Control Systems 32, 6 (Dec.2012), 48–75. DOI:DOI:
[33]
Nguyen Van Huynh, Dinh Thai Hoang, Xiao Lu, Dusit Niyato, Ping Wang, and Dong In Kim. 2018. Ambient backscatter communications: A contemporary survey. IEEE Communications Surveys & Tutorials 20, 4 (2018), 2889–2922. DOI:DOI:
[34]
Ge Wang, Chen Qian, Kaiyan Cui, Xiaofeng Shi, Han Ding, Wei Xi, Jizhong Zhao, and Jinsong Han. 2020. A universal method to combat multipaths for RFID sensing. In IEEE INFOCOM 2020 - Proceedings of the IEEE Conference on Computer Communications. 277–286. DOI:DOI:
[35]
Haoyu Wang and Wei Gong. 2021. RF-Pen: Practical real-time RFID tracking in the air. IEEE Transactions on Mobile Computing 20, 11 (Nov.2021), 3227–3238. DOI:DOI:
[36]
Jeen-Shing Wang and Fang-Chen Chuang. 2012. An accelerometer-based digital pen with a trajectory recognition algorithm for handwritten digit and gesture recognition. IEEE Transactions on Industrial Electronics 59, 7 (July2012), 2998–3007. DOI:DOI:
[37]
Wikipedia. 2023. Cubic hermite spline. Wikipedia (April2023). Retrieved April 30, 2023 from https://en.wikipedia.org/w/index.php?title=Cubic_Hermite_spline&oldid=1150323690
[38]
Chenren Xu, Lei Yang, and Pengyu Zhang. 2018. Practical backscatter communication systems for battery-free Internet of Things: A tutorial and survey of recent research. IEEE Signal Processing Magazine 35, 5 (Sept.2018), 16–27. DOI:DOI:
[39]
Chao Yang, Lingxiao Wang, Xuyu Wang, and Shiwen Mao. 2021. Meta-pose: Environment-adaptive human skeleton tracking with RFID. In Proceedings of the 2021 IEEE Global Communications Conference (GLOBECOM’21). 01–06. DOI:DOI:
[40]
Lei Yang, Yekui Chen, Xiang-Yang Li, Chaowei Xiao, Mo Li, and Yunhao Liu. 2014. Tagoram: Real-time tracking of mobile RFID tags to high precision using COTS devices. In Proceedings of the 20th Annual International Conference on Mobile Computing and Networking (MobiCom ’14). ACM, New York, NY, USA, 237–248. DOI:DOI:
[41]
Lingxiao Zheng, Xingqun Zhan, and Xin Zhang. 2020. Nonlinear complementary filter for attitude estimation by fusing inertial sensors and a camera. Sensors 20, 23 (Jan.2020), 6752. DOI:DOI:

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  1. Stabilizing Dynamic Backscatter for Swift and Accurate Object Tracking

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    Published In

    cover image ACM Transactions on Sensor Networks
    ACM Transactions on Sensor Networks  Volume 20, Issue 5
    September 2024
    349 pages
    EISSN:1550-4867
    DOI:10.1145/3618084
    • Editor:
    • Wen Hu
    Issue’s Table of Contents

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    Association for Computing Machinery

    New York, NY, United States

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    Publication History

    Published: 20 September 2024
    Online AM: 12 August 2024
    Accepted: 24 July 2024
    Revised: 19 July 2024
    Received: 29 January 2024
    Published in TOSN Volume 20, Issue 5

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    1. Backscatter
    2. tracking
    3. accelerometer

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    • Research-article

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    • National Key R&D Program of China
    • NSFC
    • Key Research Program of Frontier Sciences, CAS
    • Hefei Municipal Natural Science Foundation
    • Fundamental Research Funds for the Central Universities

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