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RF-Eye: Training-Free Object Shape Detection Using Directional RF Antenna

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Mobile and Ubiquitous Systems: Computing, Networking and Services (MobiQuitous 2022)

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Abstract

Detecting object shape presents significant values to applications such as Virtual Reality, Augmented Reality and surveillance. Traditional solutions usually deploy camera on site and apply image processing algorithms to obtain object shape. Wearable solutions require target to wear some devices, and apply machine learning algorithms to train and recognize object behaviors. The recent advances in Radio Frequency (RF) technology offer a device-free solution to detect object shape, however a number of research challenges exist. This paper presents RF-Eye, a novel RF-based system to detect object shape without training in indoor environments. We design and implement Linear Frequency Modulated baseband signal, making it suitable for detecting object shape. We also apply the narrow pulse signal reflections and Doppler Frequency Shift to detect the full image of object shape. We implement RF-Eye on a Universal Software Radio Peripheral device. Our experimental results show that RF-Eye achieves 100% successful rate, and it performance is reliable in complicated cases.

This research was supported in part by NSFC 61872247.

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Authors and Affiliations

  1. RMIT University, 124 La Trobe Street, Melbourne, VIC, 3000, Australia

    Weiling Zheng

  2. Shenzhen University, Nanhai Avenue 3688, Shenzhen, China

    Weiling Zheng, Dian Zhang & Peng Ji

  3. Macquarie University, Balaclava Road, North Ryde, NSW, 2109, Australia

    Tao Gu

Authors
  1. Weiling Zheng
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  2. Dian Zhang
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  3. Peng Ji
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  4. Tao Gu
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Corresponding author

Correspondence to Dian Zhang .

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Editors and Affiliations

  1. University of Pittsburgh, Pittsburgh, PA, USA

    Shangguan Longfei

  2. Microsoft Research, Redmond, WA, USA

    Priyantha Bodhi

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Zheng, W., Zhang, D., Ji, P., Gu, T. (2023). RF-Eye: Training-Free Object Shape Detection Using Directional RF Antenna. In: Longfei, S., Bodhi, P. (eds) Mobile and Ubiquitous Systems: Computing, Networking and Services. MobiQuitous 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 492. Springer, Cham. https://doi.org/10.1007/978-3-031-34776-4_28

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  • DOI: https://doi.org/10.1007/978-3-031-34776-4_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-34775-7

  • Online ISBN: 978-3-031-34776-4

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