Abstract

This paper proposes a detection technique for the chipless RFID system. In the proposed technique, the experiments for measuring the scattering responses of all possible tags were conducted first in a free-space anechoic chamber in order to avoid the effect of unwanted signals due to the environment. The responses of all possible tags were exploited in order to extract poles, including natural frequencies and damping factors, by using the short-time matrix pencil method. All extracted poles successively chosen from the late-time portions were exploited to create the decision boundary by using the k- nearest neighbor algorithm. In order to validate the robustness of the proposed detection technique, experiments with the chipless RFID system with tags attached to containers, i.e. parcel and plastic boxes, were conducted. Poles extracted from the response of the tag attached to a container were fed to the decision boundary for ID detection. The poles that had fallen into the region labeled as logic “1” were detected as logic “1,” and vice versa . The experiment results showed that the attachment of the tags to the containers caused a change in the poles. The conventional technique using only natural frequencies has exhibited poor performance regarding tag ID detection. On the other hand, the proposed detection technique achieved a 100% detection rate, although the extracted poles used to detect the bit logic were disturbed by the container. The experimental results confirm the superiority of the proposed system over conventional chipless RFID detection. Moreover, the proposed technique can be considered a robust detection technique.

Highlights

  • Chipless radio frequency identification (RFID) technology has received considerable interest as a promising solution for many applications in sensing and tracking, such as sensors for structural health monitoring, tracking of inventory in retail settings, and smart packaging

  • The short-time matrix pencil method (STMPM) was applied to the chipless RFID applications, and to the radar target identification, as we proposed in [12], [13], [15]-[17]

  • It has clearly shown that only the natural frequency rather than poles was employed to represent the tag ID. These approaches have employed poles extracted by using the matrix pencil method (MPM) or STMPM to represent the data encoded in the chipless RFID tag, they have not realized the necessity of the detection technique for tag identification

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Summary

INTRODUCTION

Chipless radio frequency identification (RFID) technology has received considerable interest as a promising solution for many applications in sensing and tracking, such as sensors for structural health monitoring, tracking of inventory in retail settings, and smart packaging. The main limitation of the frequency-based chipless RFID technology is the bandwidth required in order to increase the information capacity. These approaches have employed poles extracted by using the MPM or STMPM to represent the data encoded in the chipless RFID tag, they have not realized the necessity of the detection technique for tag identification. This paper extends and validates the use of poles to represent the tag ID and introduces the detection technique using the k-nearest neighbor (k-NN) algorithm This algorithm, one of the most popular non-parametric classifications, has been widely used with many applications such as online handwritten signature detection [21], the classification of big data in healthcare [22], and pattern recognition in cloud chipless RFID processing [23].

PROPOSED TECHNIQUE
DECISION-BOUNDARY CREATION
DETECTION OF THE CHIPLESS RFID SYSTEM
Findings
CONCLUSION
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