Reliability study for vibration measurement via dual passive RFID tags

This study explores a vibration measurement technique utilizing dual passive RFID tags. A primary challenge in such systems lies in channel interference caused by the coupling effect of multiple tags, which significantly compromises the accuracy and stability of vibration analysis. Furthermore, the selection of inappropriate parameters in conventional compressive sensing (CS) methods tends to exacerbate spectral interference under conditions of sparse sampling. To overcome these limitations, this paper proposes an adaptive CS method that dynamically adjusts reconstruction parameters, such as the sensing matrix dimension and signal sparsity level, with reference to the fundamental characteristics of the obtained signal. This adaptive mechanism not only mitigates electromagnetic coupling interference between tags but also extends the measurable frequency range beyond the Nyquist limit associated with low-rate RFID sampling. Experimental results across a range of vibration frequencies demonstrate that the proposed method enhances spectral clarity, improves frequency resolution, and maintains robust signal reconstruction in densely deployed dual-tag environments. These findings underscore the potential of the method as a scalable and reliable solution for high-precision vibration sensing in RFID-based applications.