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Evaluation of a U-Shaped Convolutional Neural Network for RCS based Chipless RFID Systems

Rather, Nadeem; Simorangkir, Roy B. V. B.; Buckley, John L.; O’Flynn, Brendan; Tedesco, Salvatore

Authors

Nadeem Rather

John L. Buckley

Brendan O’Flynn

Salvatore Tedesco



Abstract

In this paper, for the first time, a one-dimensional convolutional neural network using a U-shaped architecture is evaluated in the context of radar cross section (RCS) based chipless RFID (CRFID) systems. A 3-bit CRFID tag is utilised to create eight discernible RCS signatures representing identification numbers. A dataset of 9,600 measured RCS signatures was utilised for training, validating, and testing the model. The dataset was collected by placing the tag on varying surface shapes, orientations, and read ranges to enable robust detection. The root mean square error (RMSE) metric was used to assess the model’s performance. The achieved RMSE was 0.11 (1.5%). The low RMSE score demonstrates the effectiveness that this type of architecture has in accurately detecting and generalizing the encoded information from the RCS signatures.

Citation

Rather, N., Simorangkir, R. B. V. B., Buckley, J. L., O’Flynn, B., & Tedesco, S. (2023). Evaluation of a U-Shaped Convolutional Neural Network for RCS based Chipless RFID Systems. In 2023 IEEE 13th International Conference on RFID Technology and Applications (RFID-TA). https://doi.org/10.1109/rfid-ta58140.2023.10290467

Conference Name 2023 IEEE International Conference on RFID Technology and Applications (RFID-TA)
Conference Location Aveiro, Portugal
Start Date Sep 4, 2023
End Date Sep 6, 2023
Acceptance Date Sep 4, 2023
Online Publication Date Oct 27, 2023
Publication Date Oct 27, 2023
Deposit Date May 7, 2024
Publisher Institute of Electrical and Electronics Engineers
Series ISSN 2377-018X
Book Title 2023 IEEE 13th International Conference on RFID Technology and Applications (RFID-TA)
ISBN 9798350333541
DOI https://doi.org/10.1109/rfid-ta58140.2023.10290467
Public URL https://durham-repository.worktribe.com/output/2434191