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Abstract In modern times, antenna design has become more demanding than ever. The escalating requirements for performance and functionality drive the development of intricately structured antennas, where parameters must be meticulously adjusted to achieve peak performance. Often, global adjustments to geometry are necessary for optimal results. However, direct manipulation of antenna responses evaluated with full-wave electromagnetic (EM) simulation models using conventional nature-inspired methods entails significant computational costs. Alternatively, surrogate-based techniques show promise but are impeded by dimensionality-related challenges and nonlinearity of antenna outputs. This study introduces an innovative technique for swiftly optimizing antennas. It leverages a machine learning framework with an infill criterion employing predicted enhancement of the merit function, utilizing a particle swarm optimizer as the primary search engine, and employs kriging for constructing the underlying surrogate model. The surrogate model operates within a reduced-dimensionality domain, guided by directions corresponding to maximum antenna response variability identified through fast global sensitivity analysis, tailored explicitly for domain determination. Operating within this reduced domain enables building dependable metamodels at a significantly lower computational cost. To address accuracy loss resulting from dimensionality reduction, the global optimization phase is supplemented by local sensitivity-based parameter adjustment. Extensive comparative experiments involving various planar antennas demonstrate the competitive operation of the presented technique over machine learning algorithms operating in full-dimensionality space and direct EM-driven bio-inspired optimization techniques.

Abstract Behavioral models have garnered significant interest in the realm of high-frequency electronics. Their primary function is to substitute costly computational tools, notably electromagnetic (EM) analysis, for repetitive evaluations of the structure under consideration. These evaluations are often necessary for tasks like parameter tuning, statistical analysis, or multi-criterial design. However, constructing reliable surrogate models faces several challenges, including the nonlinearity of circuit characteristics and the vast size of the parameter space, encompassing both dimensionality and design variable ranges. Additionally, ensuring the validity of the model across broad geometry/material parameter and frequency ranges is crucial for its utility in design. The purpose of this paper is to introduce an innovative approach to cost-effective and dependable behavioral modeling of microwave passives. Central to our method is a fast global sensitivity analysis (FGSA) procedure, which is devised to identify correlations between design parameters and quantify their impacts on circuit characteristics. The most significant directions identified through FGSA are utilized to establish a reduced-dimensionality domain. Within this domain, the model may be constructed using a limited amount of data samples while capturing a significant portion of the circuit response variability, rendering it suitable for design purposes. The outstanding predictive capability of the proposed model, its superiority over traditional techniques, and its readiness for design applications are demonstrated through the analysis of three microstrip circuits of diverse characteristics.

Abstract Novel designs of frequency selective surface (FSS) are presented for wideband applications in X, Ku and mmWave (millimeter Wave) bands. Two identical metallic layers of FSS are imprinted on both sides of the RO4003 substrate. The geometry parameters are optimized to maximize the bandstop at the specified in-band maximum transmission level of −10 dB; satisfaction of the latter condition is enforced through appropriate formulation and handling of the design constraints. The proposed structure is versatile and can be readily re-designed for various operating bands. For the sake of illustration, two instances of the FSS were developed. Design 1 exhibits broad bandstop of 9.8 GHz at the X- and Ku-bands, whereas the bandstop of Design 2 is 33.5 GHz at the mmWave band. The two FSS unit cell designs share the same base topology, but specific dimensions are adjusted to operate within the lower and the higher bands, respectively. The unit cell is symmetrical, therefore, ensures an excellent resonance stability performance with respect to different polarizations (TE and TM) and incidence angles. For proof of concept only FSS Design 1 is fabricated and measured in an anechoic chamber. The simulated and measured results exhibit good agreement. Extensive benchmarking against state-of-the-art FSS designs from the literature corroborates the advantages of the proposed topology in terms of design novelty, topological versatility, compact size, and wide bandstop response as compared to the previously available designs.

Prototype measurements are the key step in the development of antenna structures. Typically, their far-field characteristics are validated in expensive, dedicated facilities such as open range sites, or anechoic chambers. Despite being necessary for obtaining high-precision data (e.g., for device qualification), the use of costly infrastructure might not be fully justified when the main goal of measurements includes demonstration of the methodology behind determination of the performance figures of interest (e.g., for the purpose of teaching), or rough validation of the EM simulation model correctness. From this perspective, systems for far-field measurements in non-anechoic environments represent an interesting alternative to the utilization of the state-of-the-art equipment and facilities. Despite their proven usefulness, the mentioned systems are normally constructed around the expensive, laboratory-grade equipment, which contradicts the whole concept of low-cost measurements. This paper discusses a cost-efficient, mobile system for experimental validation of antennas. Its main components include the in-house developed rotary heads, an open-hardware-based vector network analyzer, and the measurements post-processing software. The cost of the system amounts to only around 3630 USD. The capabilities of the device have been demonstrated through measurements of two antenna structures. The considered performance figures include radiation pattern and single-direction gain vs. frequency. Comparisons against the measurements performed in benchmark conditions (anechoic chamber), as well as using professional network analyzer have also been provided. Furthermore, the documentation that facilitates the construction of the system components is shared in an online repository.

This paper presents a novel miniature interdigitated ultra-high frequency (UHF) radio frequency identification (RFID) tag antenna that can be placed on metallic objects. The tag structure comprises two horizontal strip lines, each loaded with seven identical open stubs, and an integrated circuit (IC) chip connected directly to the feed lines in the middle of the structure. The perfect match to the IC chip’s impedance is realized by adjusting the length of the loaded open stubs and the spaces between the stubs. Molding the antenna’s geometry can be applied to realize conjugated impedance with any sort of IC chip due to the flexibility of the tag structure. It is fabricated on a single Polytetrafluoroethylene (PTFE) substrate. Moreover, the proposed structure does not involve any metallic vias or shorting walls, which makes its construction simple and suitable for mass production. The tag of the size of $55.2mm\times 44.2mm\times 1.5mm$ yields a total realized gain of −4.11 dB at the North American band (902 – 928 MHz) while being placed on a $20cm\times 20cm$ metallic plate. The measured detection distance is $8.14~m$ on metallic objects and $5~m$ in the free space. A good match between the measured and simulated results is observed.