Towards Large-Scale RFID Positioning : A Low-cost, High-precision Solution Based on Compressive Sensing

Chang, Liqiong and Li, Xinyi and Wang, Ju and Meng, Haining and Chen, Xiaojiang and Fang, Dingyi and Tang, Zhanyong and Wang, Zheng (2018) Towards Large-Scale RFID Positioning : A Low-cost, High-precision Solution Based on Compressive Sensing. In: 2018 IEEE International Conference on Pervasive Computing and Communications (PerCom) :. IEEE. ISBN 9781538632246

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Abstract

RFID-based positioning is emerging as a promising solution for inventory management in places like warehouses and libraries. However, existing solutions either are too sensitive to the environmental noise, or require deploying a large number of reference tags which incur expensive deployment cost and increase the chance of data collisions. This paper presents CSRP, a novel RFID based positioning system, which is highly accurate and robust to environmental noise, but relies on much less reference tags compared with the state-of-the-art. CSRP achieves this by employing an noise-resilient RFID fingerprint scheme and a compressive sensing based algorithm that can recover the target tag's position using a small number of signal measurements. This work provides a set of new analysis, algorithms and heuristics to guide the deployment of reference tags and to optimize the computational overhead. We evaluate CSRP in a deployment site with 270 commercial RFID tags. Experimental results show that CSRP can correctly identify 84.7% of the test items, achieving an accuracy that is comparable to the state-of-the-art, using an order of magnitude less reference tags.

Item Type:
Contribution in Book/Report/Proceedings
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©2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.©2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ID Code:
89133
Deposited By:
Deposited On:
12 Dec 2017 08:56
Refereed?:
Yes
Published?:
Published
Last Modified:
11 Aug 2024 23:15