This invited, extended, paper compares and contrasts a number of different near-field (NF) to far-field (FF) transformation algorithms that can be used for the purpose of processing NF data acquired using multi-axis industrial robots. The merits and limitations of these various, commonly encountered algorithms are highlighted with comparison FF data presented across a frequency range spanning 3–15 GHz. Crucially, the paper explores the viability of using mixed mode acquisition geometries when performing antenna gain measurements where, prior to this work, several of the transforms yielded different transform gains, and electrical lengths. Here, we verify that at 8 GHz and above, where truncation effects were minimal, for a circa 30 dBi gain (at 8 GHz) test antenna the FF peaks were in agreement to better than ±0.02 dB, at 3σ irrespective of the acquisition geometry and transform algorithm used. In this invited, extended work, the existing simulation results are augmented with experimental results obtained from planar and spherical NF measurements of a pyramidal horn taken using a dual robotic antenna measurement system and a consistent distributed RF subsystem.

We present a higher-order spectral element method (SEM) for analyzing eccentric anisotropic multilayered waveguides. The formulation uses conformal transformation optics to map the original eccentric waveguide to an equivalent concentric one. This transformation is extended to handle anisotropic non-reciprocal media characterized by non-symmetric and non-Hermitian tensors. In the transformed concentric domain, higher-order two-dimensional basis functions associated with the zeros of the completed Lobatto polynomial are used to expand the fields. To simulate radially unbounded problems, we employ a complex-stretched perfectly matched layer to mimic open space. The method is validated with radially bounded two-layer and three-layer waveguides and radially unbounded three-layer waveguides. Comparisons with the finite element method (FEM) demonstrate that our SEM approach requires significantly fewer degrees of freedom than FEM.

This paper describes the application of the differential evolution (DE) method for synthesizing radiation patterns of two 4×4 microstrip planar antenna arrays. The performance of the DE algorithm was evaluated by optimizing beam steering with simultaneous sidelobe level (SLL) control. Additionally, the algorithm optimizes the cross-polarization decoupling (XPD) to improve the polarization purity. In the optimization process, the active element patterns were incorporated into the DE algorithm to account for mutual coupling and truncation of the ground plane and the substrate in the determination of the excitation coefficients of each array element. The results demonstrate that the DE method can be effectively used to optimize radiation patterns particularly in terms of main beam pointing direction, SLL control, and XPD with fast convergence and low computational cost.

INCUS (INvestigation of Convective UpdraftS) is a NASA Earth Science mission scheduled to launch in 2026. The goal of the mission is to study in detail how water vapor and droplets move inside tropical storms and thunderstorms and understand their effects on weather and climate models. To carry out this study, the mission will use three almost identical SmallSats, each equipped with a Raincube-heritage Ka-band radar. The deployable mesh reflector antenna is a new 1.6 m design provided by Tendeg, which is fed using a seven-horn feed assembly to generate overlapping secondary beams. This paper discusses the approach used to design and fabricate the feed assembly and presents the measured and calculated RF performance parameters.

Accurate channel characterization is extremely helpful in channel estimation, channel coding, and many other parts of communication system design and can effectively reduce overhead. Ray tracing (RT) shows accurate channel reconstruction for specific maps, but the multipath propagation in indoor scenes is far more complex than in outdoor scenes leading to a challenge for RT. This work presents and validates an RT tool for a massive multiple-input multiple-output (MIMO) system in the millimeter-wave frequency bands with the associated channel beamforming algorithm and provides ideas for channel estimation algorithm in subsequent MIMO systems. The impact of the order of interactions, e.g. reflections and diffractions on the channel impulse response reconstruction are analyzed in the RT simulation. The comparison between RT simulated and measured results shows a reasonable level of agreement. The presented RT tool that can provide complete and accurate channel information is of high value for the design of reliable communication systems.

Microwaves (MWs) have emerged as a promising sensing technology to complement optical methods for monitoring floating plastic litter. This study uses machine learning (ML) to identify optimal MW frequencies for detecting floating macroplastics (>5 cm) across S, C, and X-bands. Data were obtained from dedicated wideband backscattering radio measurements conducted in a controlled indoor scenario that mimics deep-sea conditions. The paper presents new strategies to directly analyze the frequency domain signals using ML algorithms, instead of generating an image from those signals and analyzing the image. We propose two ML workflows, one unsupervised, to characterize the difference in feature importance across the measured MW spectrum, and the other supervised, based on multilayer perceptron, to study the detection accuracy in unseen data. For the tested conditions, the backscatter response of the plastic litter is optimal at X-band frequencies, achieving accuracies up to 90% and 80% for lower and higher water wave heights, respectively. Multiclass classification is also investigated to distinguish between different types of plastic targets. ML results are interpreted in terms of the physical phenomena obtained through numerical analysis, and quantified through an energy-based metric.

Multipath components (MPCs) are both the challenge and the resources to exploit in high-frequency wireless communication, especially in environments with complex reflections. On the one hand, late-arriving MPCs cause inter-symbol interferences in digital communication. On the other hand, techniques such as multiple-input multiple-output and rake receivers have been widely applied to utilize the information carried in the math-path components. To this end, identifying and clustering MPCs is the foundation for tackling the challenges and boosting the utilization of reliable and correct information. Past research focuses either on extracting the path information or on clustering the extracted components. In this paper, we propose a complete workflow that performs identification as well as clustering of MPCs. We extend our previous work in clustering algorithms to indoor propagation measurements of three different frequency bands, as well as multiple transmitter–receiver locations. We verify that the fast attenuation of terahertz-band signals results in clear separations of peaks in measurements, which in turn facilitates the identification and clustering solutions. The ease of application highlights the wide-applying potential of high-frequency communication.

Several breast microwave sensing (BMS) systems have shown encouraging results as a potential breast cancer detection tool. The existing systems in the literature have diverse designs, equipment, measurement protocols, and analysis methods. However, there is relatively little investigation on the impact and performance of varying system designs. This work compares the impact of system design parameters on three existing BMS systems. The first system, a bed-based system, was designed for use in a permanent clinic. The second system, a bench-top system, was created for laboratory research. The third system, a portable system, was designed for use in low-income and remote communities. The bed-based system had the highest resolving capabilities, achieving a spatial resolution of 12.4 ± 0.5 mm. Additionally, the bed system had the highest signal-to-noise ratio of 26 ± 1 dB. The portable system had the least intensity dependence on polar positions within the imaging chamber. The bed system had the highest contrast between tumor- and adipose-mimicking materials. However, the contrast of tumor- and fibroglandular-mimicking materials was similar for each system. By comparing and evaluating the performance of multiple BMS systems, we improve our understanding of system design, allowing for potential studies into an ideal BMS system.

In this paper, we present the design, simulation, fabrication, and measurements of an on-chip dielectric resonator (DR)-fed millimeter-wave high-gain antenna system with in-antenna power combining capability. A low-profile resonant cavity antenna is fed by four spherical DR, showcasing the antenna’s multi-feed capabilities. Each DR is fed by two microstrip resonators located diagonally opposite on a planar circuit board and are excited via coaxial connectors. The design incorporates a printed partially reflecting superstrate, reducing the antenna’s overall size and profile while simultaneously enhancing directivity by approximately $10\,\mathrm{dB}$ at the design frequency of $30\,\mathrm{GHz}$. The antenna exhibits wideband matching. Key performance metrics, such as directivity, gain, beamwidth, and bandwidth, predicted by full-wave electromagnetic simulations align well with the results from experimental measurements.

The digitalization of the mining industry requires wireless connectivity for real-time status indications, remote-controlled mining operations, and autonomous driving vehicles in tunnels. This paper presents a wideband radio propagation measurement system and provides radio channel measurement results for data at 5G frequency range 1 and frequency range 2 bands recorded in Sandvik’s test mine in Tampere, Finland. The measured signal attenuation due to the blocking of the tunnel by a scoop and a large loader vehicle is found to be in the range of 10 dB at 3.5 GHz. The radio signal level attenuates significantly when the other end of the link moves into a side tunnel from the main tunnel. The measured signal attenuation rates in tunnel crossroads at 3.5 GHz were 10 and 15 dB/m. The root mean square delay spreads in the two crossroads were 3–10 ns, corresponding to coherence bandwidths of 300 and 100 MHz, respectively. The signal reflections from the tunnel walls were studied at a 26.5 GHz frequency by steering the transmission antenna azimuthally. The FR2 measurement results at 6 m inside the side tunnel indicate strong reflections from the side walls, evident from the path length amplitude results.

The radome of weather radars can be covered with a layer of water, degrading the quality of the radar products. Considering a simplified setup with a planar replica of the Swiss weather radars’ radome, we measure and model analytically its scattering parameters, with and without water. The measured reflectance of the dry radome replica agrees well with the one modeled according to the manufacturer specifications. Water forms droplets on the hydrophobic surface, but water films thicker than 1 mm can be created. Meteorologically more realistic thinner water films are expected on old radomes that have become hydrophilic with aging. Using hygroscopic silk and cotton tissues, we empirically imitate water films as thin as less than 0.1 mm. The measurements align with the simple analytical model of uniform plane wave incidence on the radome and water film but could be further improved by taking refraction and bending of the radome replica into account. Simulations with the General Reflector Antenna Software Package (GRASP) from TICRA complement the study for a representative setup with a spherical radome.

Two-dimensional (2D) leaky-wave antennas (LWAs) are commonly designed to radiate pencil beams at broadside and/or scanned conical beams. Recently, the possibility to radiate narrow null patterns at broadside has also been preliminarily explored. In this work, we first review the design rules to obtain a pencil beam from an infinite 2D LWA and then show how they change for having a beam with a narrow null at broadside. The effects of antenna truncation are also accounted for in both cases, and numerical results show how the optimum conditions are in turn affected. Finally, full-wave validations of practical structures excited with either horizontal or vertical dipoles validate the analysis.

In this study, we aimed to develop high permittivity $\text{TiO}_{2}$ ceramics ideal for the fabrication of all-dielectric metamaterials (ADM) operational in the terahertz frequency. $\text{TiO}_{2}$ ceramic pellets have been fabricated from a commercial powder. A comparative analysis was conducted between spark plasma sintering (SPS) and conventional sintering process. Characterizations were then carried out in the range of 0.2–1.4 THz using THz time-domain spectroscopy. We observed that the samples fabricated by the SPS and post-annealing treatment exhibit a high permittivity associated with minimal loss (${\varepsilon^{ \prime}} \simeq$ 100 and $\tan\delta \lt $ 0.015). These characteristics make these samples optimal candidates for achieving a negative or near-zero effective index in all-dielectric metamaterials. In addition, four micro-structuring processes were investigated to produce ADM operating in the terahertz range from the ceramics:

(i) micro-molding,

(ii) direct $\text{TiO}_{2}$ etching by inductively coupled plasma,

(iii) saw cutting and

(iv) femtosecond laser etching.

Wireless channel propagation parameter estimation forms the foundation of channel sounding, estimation, modeling, and sensing. This paper introduces a deep learning approach for joint delay and Doppler estimation from frequency and time samples of a radio channel transfer function.

Our work estimates the 2D path parameters from a channel impulse response containing an unknown number of paths. Compared to existing deep learning-based methods, the parameters are not estimated via classification but in a quasi-grid-free manner. We employ a deterministic preprocessing scheme that incorporates a multichannel windowing to increase the estimator’s robustness and enables the use of a convolutional neural network (CNN) architecture. The proposed architecture then jointly estimates the number of paths along with the respective delay and Doppler shift parameters of the paths. Hence, it jointly solves the model order selection and parameter estimation task. We also integrate the CNN into an existing maximum-likelihood estimator framework for efficient initialization of a gradient-based iteration, to provide more accurate estimates.

In the analysis, we compare our approach to other methods in terms of estimate accuracy and model order error on synthetic data. Finally, we demonstrate its applicability to real-world measurement data from a anechoic bistatic RADAR emulation measurement.

This paper presents a multibeam dielectric rod antenna for mm-wave wireless power transfer (WPT) applications. The proposed solution utilizes its unique multibeam setup which allows the generation of adjustable beams simultaneously, without the need for an additional beamforming network. To enhance the compactness of the system, each Rexolite rod is fed through an annular slot etched on a Rogers RO4003. The generated beams are steered toward the desired directions by adjustment in the configuration of these rods. The final configuration consists of five rods that were fabricated and measured. In this configuration, a beam coverage between $-30^{\circ}$ and 30∘ can be obtained, while in the frequency of interest, a gain value above $12\,\mathrm{dBi}$ is achieved. With its adjustable configuration, the proposed solution can be adapted to different operating scenarios. Moreover, the low cost and flexibility of the solution make it a promising candidate for Radio Frequency Wireless Power Transfer (RF-WPT) Internet of things applications.

Acute respiratory distress syndrome (ARDS) is a critical lung condition caused by trauma or infection. This study explores the development and evaluation of human lung phantoms to investigate the feasibility of using microwave frequencies for ARDS detection. Both physical semisolid phantoms and their numerical models were developed in inflated and deflated states to replicate the dielectric properties of healthy and affected lungs. Three phantom sets with varying water and air content were fabricated to simulate different stages of respiratory distress. The geometric parameters of the phantoms were derived from CT scans of 166 ARDS patients. Dielectric permittivity and conductivity were measured using a Keysight N1501A dielectric probe over a 0.5–13 GHz range, showing strong agreement with IFAC’s reference data. To validate the models, horn antennas operating between 8.2–12.4 GHz were used to measure S-parameters (S11 and S21) in both physical and numerical phantoms. The results demonstrated consistent changes in transmission and reflection characteristics corresponding to variations in lung volume and dielectric properties. These findings support the potential of microwave imaging as a non-invasive tool for early ARDS detection by effectively distinguishing between healthy and distressed lung states based on measurable electromagnetic response.