Detection of Minimum Geometrical Variation by Free-Space-Based Chipless Approach and its Application to Authentication

A free-space-based chipless approach using a second-order bandpass filter model is presented in this letter to detect minimum geometrical variations along the dimensions of a C-folded scatterer. With the help of this model, further randomness inherent in fabrication process can also be analyzed and forecast. Quad C-folded scatterers are used to realize chipless tags and three groups of tags exhibiting distinct arms' length are fabricated. A cosine similarity function is then used to evaluate the similarity rate of electromagnetic signatures reflected by tags coming from different groups. Experimental results performed in a realistic outdoor environment show that it is possible to discriminate two tags which differ from each other by a mean variation of around 25 $\mu \text{m}$ along the arms' length. Finally, the proposed analytical model is capable to dissociate the tags by using merely two extracted aspect-independent quantities: the frequency of resonance and the quality factor.