Local Sensitivity Analysis and Monte Carlo Simulation to Examine the Effects of Chipless RFID Measurement Uncertainties—Part I: Misalignment-Based Uncertainty

Abstract

Measurement and response decoding is an ongoing challenge in the chipless radio-frequency identification (RFID) field. Measurement uncertainties, including tag/reader misalignment, radar cross-section or S-parameter error, and clutter, can cause response distortions, such as magnitude changes and resonant frequency shifts. These response distortions can lead to the improper assignment of a binary code or sensing parameter (i.e., improper decoding). This work aims to use local sensitivity analysis and Monte Carlo simulation to fully characterize the effects of misalignment, response parameter measurement error (e.g., vector network analyzer S-parameter error), and clutter on chipless RFID tag responses. From this type of comprehensive characterization, conclusions are drawn about the identification (ID) and sensing capabilities of the tags. In this work, the simulations are performed for two specific tags and the results are then corroborated with measurements of one of the tags. While the work is done for a near-field monostatic measurement setup, it is presented such that the same procedures can be applied to other tags and measurement setups, including far-field scenarios. Thus, a novel comprehensive tag performance assessment framework is provided. This work is divided into two parts. In Part I, the effects of tag/reader misalignment uncertainty are examined in depth through both simulations and measurements. In Part II, the effects of S-parameter error, clutter-based uncertainty, and the combination of these uncertainties with misalignment uncertainty are investigated. An example demonstrating the application of this tag performance assessment framework is also provided in Part II.