research-article

LSAB: Enhancing Spatio-temporal Efficiency of AoA Tracking Systems

Authors:

Qiongzheng LinAuthors Info & Claims

ACM Transactions on Sensor Networks, Volume 18, Issue 4

Article No.: 58, Pages 1 - 25

https://doi.org/10.1145/3534123

Published: 29 November 2022 Publication History

Abstract

Estimating the angle-of-arrival (AoA) of an RF source by using a large-sized antenna array is a classical topic in wireless systems. However, AoA tracking systems are not yet used for Internet of Things (IoT) in the real world due to their unaffordable cost. Many efforts, such as a time-sharing array, emulated array, and sparse array, were recently made to cut the cost. This work introduces a log-spiral antenna belt (LSAB), a new novel sparse “planar array” that could estimate the AoA of an IoT device in 3D space by using a few antennas connected to a single timeshare channel. Unlike the conventional arrays, LSAB deploys antennas on a log-spiral-shaped belt in a non-linear manner, following the theory of minimum resolution redundancy newly discovered in this work. One physical 8 × 8 uniform planar array (UPA) and four logical sparse arrays, including LSAB, were prototyped to validate the theory and evaluate the performance of sparse arrays. The extensive benchmark demonstrates that the performance of LSAB was comparable to that of a UPA, with similar degree of resolution; and LSAB could provide over 40% performance improvement than existing sparse arrays. We also prototyped a second LSAB adapted to an RFID system for localizing RFID tags at centimeter-level accuracy.

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Index Terms

LSAB: Enhancing Spatio-temporal Efficiency of AoA Tracking Systems
1. Networks
  1. Network services
    1. Location based services

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Published In

cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 18, Issue 4

November 2022

619 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/3561986

Editor:
Yunhao Liu
Tsinghua University, China

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Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 29 November 2022

Online AM: 26 May 2022

Accepted: 27 April 2022

Received: 25 February 2022

Published in TOSN Volume 18, Issue 4

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NSFC Excellent Young Scientists Fund (Hong Kong and Macau)
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Cited By

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https://dl.acm.org/doi/10.1145/3633333
Zeng YMai SYan WHu H(2024)Multimodal Reaction: Information Modulation for Cross-Modal Representation LearningIEEE Transactions on Multimedia10.1109/TMM.2023.329333526(2178-2191)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TMM.2023.3293335
Su TLiang QZhang JYu ZXu ZWang GLiu X(2023)Deep Cross-Layer Collaborative Learning Network for Online Knowledge DistillationIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2022.322201333:5(2075-2087)Online publication date: 1-May-2023
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Jiang JLiu ZZheng N(2023)Correlation Information Bottleneck: Towards Adapting Pretrained Multimodal Models for Robust Visual Question AnsweringInternational Journal of Computer Vision10.1007/s11263-023-01858-y132:1(185-207)Online publication date: 28-Aug-2023
https://dl.acm.org/doi/10.1007/s11263-023-01858-y

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