Time-Domain Electromagnetic Identification Based on Rectangular Grooves

Abstract

Unique identification of goods and products is an integral part of today's automated world. Conventional optical systems cannot be operated in environments of poor visibility. The radio-frequency identification systems require expensive development, production, and installation of passive tags. In this paper, we propose a system that stores the information necessary for the distinction of individual items into a set of grooves with different geometric properties. The individual items are then identified based on observing the response to the electromagnetic wave in the time domain. The proposed identification system benefits from the cooperation of a semi-analytical computational scheme based on the Cagniard-DeHoop Method of Moments and a global optimization algorithm that solves the inverse problem of grooves characterization. The proposed system is validated on several computational examples. Also, the resilience of the proposed system to the influence of the noise added to the observed response is investigated. Finally, the influence of reflected signals on the accuracy of the system is assessed.Unique identification of goods and products is an integral part of today's automated world. Conventional optical systems cannot be operated in environments of poor visibility. The radio-frequency identification systems require expensive development, production, and installation of passive tags. In this paper, we propose a system that stores the information necessary for the distinction of individual items into a set of grooves with different geometric properties. The individual items are then identified based on observing the response to the electromagnetic wave in the time domain. The proposed identification system benefits from the cooperation of a semi-analytical computational scheme based on the Cagniard-DeHoop Method of Moments and a global optimization algorithm that solves the inverse problem of grooves characterization. The proposed system is validated on several computational examples. Also, the resilience of the proposed system to the influence of the noise added to the observed response is investigated. Finally, the influence of reflected signals on the accuracy of the system is assessed.