Title

An Aperture Efficiency Approach for Optimization of FSS-Based Sensor Resolution

Abstract

Frequency-selective surfaces (FSSs) are periodic arrays of conductive elements, and when illuminated by electromagnetic energy, they have a specific frequency response. FSS-based sensing is a relatively new application of FSSs, and such sensors have shown promise for crack detection and strain sensing, among others. Generally, when an FSS sensor is illuminated in full, the response of the sensor is related to the entire FSS landscape. In this way, the resolution of the sensor is equal to the FSS dimensions. However, this limits localized sensing. As such, to improve the achievable resolution, the sensor must be illuminated locally for the response to be related to a specific region of the sensor. Under this approach, an FSS sensor is considered to consist of many sensor cells. Therefore, to quantify the sensor cell efficiency in terms of the illuminating footprint in order to obtain the optimum sensor cell size, an analysis approach based on the reflectarray aperture efficiency is used. As such, by maximizing the sensor cell efficiency, an optimum sensor cell size can be determined for a given illuminating footprint. This approach is applied to a grounded square-loop-based FSS sensor, with the simulation and measurement results provided. The results indicate that optimal sensor cell dimensions can be determined where the total efficiency of a given footprint is maximized. To support this, three different sensor cells are considered with the same maximum total efficiency, of which the smallest sensor cell gives the highest resolution of ~ 3 cm × 3 cm.

Department(s)

Electrical and Computer Engineering

Comments

National Aeronautics and Space Administration, Grant None

Keywords and Phrases

Aperture Efficiency; Finite Frequency-Selective Surface (FSS); FSS-Based Sensing; Illumination Efficiency; Localized Sensing; Sensor Resolution; Spill-Over Efficiency

International Standard Serial Number (ISSN)

0018-9456; 1557-9662

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2020 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

10 Apr 2020

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