A Novel Detection Method Based on Maximum-Likelihood Estimation Decoding of a 6-Bit Chipless Radio Frequency Identification Coded Tag

Abstract

The detection of chipless radio frequency identification (RFID) tags is mostly realized by vector network analyzers. In actual detection, this method is expensive and not flexible enough. A flexible new detection method implemented on the Universal Software Radio Peripheral (USRP) is proposed in this article. The measurement object is a 6-bit chipless RFID coded tag sensor based on a spiral resonator trap circuit. The power detection function of the frequency band is designed and implemented on USRP's open-source platform GNU Radio. On this basis, for chipless RFID tags with spectrum coding, a decoding identification method based on maximum-likelihood estimation is designed. The frequency-domain curve of the scattered signal of the sample label is detected by the power detection method, and the decoding and identification test of the sample label is performed by the maximum-likelihood estimation decoding identification method. It is shown that the maximum-likelihood estimation decoding algorithm based on the USRP platform proposed can be effectively implemented in passive wireless networks through experimental results, which provides a new idea for the flexible and economical RFID tag detection method.