This article addresses two primordial questions concerning angularly dispersive periodic structures. First, how does the scattering response govern electromagnetic functionality at specific angles? Second, under what conditions can perfect transmission, reflection, or absorption be achieved at given angles? To this end, a unified framework is proposed to systematically integrate angular-selective transmission, reflection, and absorption. By decomposing the total scattered field into independently controllable antenna mode scattered field (AM-SF) and structural mode scattered field (SM-SF), the framework establishes a systematic link between scattering characteristics and electromagnetic functionality. This approach offers a clear physical foundation for angular manipulation of electromagnetic waves. The proposed framework is validated through simulations of three types of angle-selective surfaces (ASSs), namely, reflection-absorption (RA), transmission-reflection (TR), and transmission-absorption (TA). Experimental measurements are further carried out for TM-polarized TR-ASS and TA-ASS, along with a dual-polarized TA-ASS. These results confirm the effectiveness of the proposed method and demonstrate a scalable design framework for diverse angular-domain filtering functionalities in RF front-ends.

Although time-modulated metasurfaces (TMMS) possess flexible beam manipulation capability, they often operate at harmonic frequencies, which weakens their practicality. To solve this problem, a method enabling TMMS to achieve beam-forming at the carrier frequency is proposed and investigated. Specifically, the phase is controlled by a reconfigurable metasurface (MS), and additional time modulation (TM) amplitude excitation is introduced by utilizing an anti-phase modulation time sequence (APMTS) to achieve complete control of the reflection coefficient for each element. The working principle is elaborated in detail, and the effectiveness of the proposed method is verified by theoretical analysis. As a proof of concept, experimental validation is then carried out using a 10 × 10 1-bit TMMS prototype. The theoretical and experimental results show that the proposed method can enable the 1-bit TMMS to have the capability of controlling the amplitude and phase independently and simultaneously at the carrier frequency. Furthermore, this paper introduces, for the first time, a rigorous efficiency definition for TMMS, followed by an accurate efficiency analysis that demonstrates the proposed method achieves higher TM efficiency in beam-forming compared to conventional methods. Benefiting from the physical perspective analysis, the proposed method is clear in principle, simple in structure, and easy to implement. It may have potential applications in wireless communications, target sensing, and radar systems.

This article establishes the theoretical and empirical separability boundary of antenna array faults under quasi-far-field (QFF) observation and proposes a regional segmentation neural network (RSNN) architecture to detect element excitation faults. By analyzing the data characteristics of the QFF region and introducing the RSNN to solve the linear operator of the inverse equation of the array pattern, the linear mapping relationship from the radiated electric field to the feed excitation state was established. The training and test samples were obtained by the rapid measurement method of QFF and input into the RSNN to train the linear constraints of the inverse equation of the pattern. The network processes four distinct excitation states to evaluate how faults impact feature extraction and classification performance. Both simulated and experimental results show successful classification and localization of all four excitation states, achieving an accuracy of 0.951 and a detection time of 0.125s. The proposed method enables efficient classification and localization of antenna array excitation faults using low computational resources, offering a high-performance diagnostic solution with accurate assessment capabilities.

A broadband dual-polarized quad-ridged horn (QRH) antenna covering 2 GHz to 14 GHz is proposed for antenna measurements and electromagnetic compatibility (EMC) testing. To achieve dual-port broadband impedance matching, a metallic ring-shaped matching block and two metallic bridges are incorporated into the feeding cavity. Additionally, the ridge profile is optimized using a fourth-order Bezier curve to ensure smooth impedance transitions, while the sidewall structure is shortened to mitigate radiation pattern distortion at high frequencies. As a result of these enhancements, the fabricated antenna prototype exhibits a reflection coefficient below -10 dB, port isolation exceeding 30 dB, a gain ranging from 6.3 dBi to 19.3 dBi, and stable, symmetrical radiation patterns without beam splitting across the entire operating band. Compared with conventional designs, the proposed antenna achieves both broader bandwidth and improved radiation stability, thereby addressing typical pattern distortion in broadband applications.

This work presents a gradual interval mapping method (IMM) integration framework for the rapid design of multiple metasurfaces. By leveraging the deep neural networks, the gradual design framework efficiently predicts both S-parameters and geometric structures using interval folding lines as input. Unlike traditional and current approaches, the proposed method integrates IMM with a filling strategy, simplifying data processing and enhancing prediction accuracy. To validate its effectiveness, three types of frequency selective surface (FSS) are designed, one of which is fabricated and experimentally measured in a microwave chamber. Simulation and measurement results confirm the superior performance of the framework, highlighting its potential for intelligent electromagnetic device design. Finally, we conclude with a short discussion of the work, including its limitations and developability.

The contradiction between low scattering and high gain is becoming increasingly prominent in stealth antenna design. In this letter, a novel passive-active hybrid absorbing-amplifying electromagnetic window (AAEW) for forward gain and backward ultra-wideband absorption is proposed. The frequency responses of an amplifier-loaded frequency selective surface (ALFSS) are matched with those of a resistive layer (RL). Consequently, the out-of-band Salisbury absorption and the in-band amplifier circuit load-matching absorption are combined to achieve continuous backward ultra-wideband absorption. Furthermore, the amplifier circuit provides gain for forward incident waves, enhancing the aperture detection range. To verify the actual performance of the AAEW structure, a prototype was designed and fabricated. Test results show that under backward wave incidence, the 90% absorption band covers 4.2–14.35 GHz (109.43%). Under forward incidence, the prototype provides gain from 8.18 GHz to 12 GHz, with a maximum gain of 10.66 dB. This work provides an effective solution for achieving radiation enhancement and ultra-wideband stealth on modern stealth platforms.

Diagnosing damage of scattering targets with multiple fault sources is highly challenging, mainly because scattering-source reconstruction is ill-posed, insufficient precision, and inadequate physical interpretability. To address this challenge, a scattering physics-driven two-stage network (SP-TN) is proposed for target damage detection. The core novelty involves the following: by employing the mapping relationship in synthetic aperture radar (SAR) imaging, a physics-driven solution for inverse scattering problems is established; integrated with physical constraints on location and structure, the underlying physical rules of damage manifestations are traced, enabling the precise scattering diagnosis. The damage detection datasets containing 1856 high-quality SAR images have been constructed to study the effects of single-point damage and multiple-point damage on feature extraction and model detection accuracy. The scattering target testing and ablation experiments demonstrate that the SP-TN achieved high-precision localization, classification, and scattering entropy analysis for single-point and multiple-point scattering damage faults with 0.92 precision, providing a novel approach for scattering damage diagnosis.

In this letter, an ultra-wideband polarization-multiplexed reconfigurable metasurface (MS) is proposed for simultaneous 1-bit programmable reflection and absorption. The unit cell is co-designed with an orthogonally symmetric topology and four triangular parasitic patches, enabling bandwidth enhancement in both the reflective and absorptive channels rather than a simple combination of two functional structures. Owing to the weak coupling between two orthogonal polarization channels, the PIN-controlled reflective response is achieved with little influence on the absorptive performance. The proposed MS provides a 1-bit phase bandwidth of 53.6% and an absorption bandwidth of 95.2%. A 10 × 10 prototype is fabricated and experimentally verified through dual-beam scattering, orbital angular momentum (OAM) vortex-beam generation, and radar cross section (RCS) reduction, demonstrating its capability for wideband polarization-decoupled wave control.

In this letter, a 1-bit ultrawideband reconfigurable reflectarray (RRA) element with improved angular stability is proposed. Based on the magneto-electric (ME) dipole, a novel central-patch probe structure is introduced, wherein two diodes are connected to opposite sides of the probe to control the two resonant modes. This configuration yields a fully symmetric RRA element, which balances and stabilizes the current distributions associated with both resonant modes, thereby enabling an ultrawideband 1-bit phase response. Furthermore, rows of metallic vias are incorporated on both sides of the element to enhance the angular stability of the 1-bit phase bandwidth. Consequently, the proposed RRA element achieves a 1-bit relative phase bandwidth of 58% (8.97 GHz to 16.44 GHz) and maintains this bandwidth at 33% for oblique incidence angles up to 50 degrees. To experimentally validate the design, a 1 & times; 2 elements prototype was fabricated and characterized using the rectangular waveguide method. The measured results exhibit good agreement with the simulations, thereby verifying the ultra-wideband performance of the proposed element. System-level simulations of a 16 & times; 16 array confirm that the proposed element significantly enhances the gain bandwidth and wide-angle scanning performances. These characteristics make the proposed RRA element a strong candidate for future radar, satellite communication, and reconfigurable intelligent surface applications.

In recent years, metasurface (MS)-enabled information encryption has emerged as a new paradigm that leverages the inherent multidimensional degree of freedom (DoF) of electromagnetic (EM) waves to construct highly secure and adaptable channels. In this paper, we extend this paradigm by developing an MS-based image encryption system that integrates multidimensional EM modulation with an additional algorithmic-layer cryptographic processing to further enhance security. In the proposed framework, a multifunctional MS acts as the physical key, while an autoencoder (AE) is introduced to retrieve the phase distributions required to configure the MS for multiplexed holographic channels across several orthogonal DoFs, including orbital angular momentum (OAM) modes, polarization states, and operating frequencies. Then, the target image is mapped onto these channels using user-configurable encoding rules, and the resulting data are further encrypted through a Feistel network and Base64 transformation. The encrypted data are finally packaged into a quick response (QR) code and transmitted to the receiver, who can recover the correct image only when both the hardware- and algorithmic-layer encryption rules are fully known. Therefore, the proposed hybrid encryption strategy offers a feasible pathway toward more versatile encrypted imaging systems and has the potential to accommodate emerging requirements in secure information exchange.

Conventional electromagnetic (EM) design is typically restricted to predefined frequency ranges. This article presents a language-driven generative framework for high-fidelity EM synthesis at arbitrary frequencies, incorporating physics-scaling-guided surrogate model (PSGSM) with vector to interval line preprocessing (VILP) and variable-controlled data collection (VCDC). The approach is defined by three methodological pillars. First, frequency scaling invariance is leveraged to decouple multiband responses into a normalized domain, enabling robust cross-frequency data/model reuse. Second, the VILP method transforms stochastic user vectors into structured, piecewise linear intervals, allowing the surrogate model to perceive continuous scaling trajectories rather than isolated points. Third, the VCDC strategy stabilizes the low-frequency resonance ( $f_{1}$ ) to isolate high-frequency variations ( $f_{2}$ ), ensuring data alignment with scaling logic and significantly enhancing sampling efficiency. The framework is validated through the design of a bandpass filter (BPF) and dual-passband frequency-selective surfaces (DP-FSSs). Experimental results from a fabricated DP-FSS prototype demonstrate high precision and flexibility in frequency-independent EM synthesis.

In this paper, a physics and statistics co-enhanced Gaussian process regression (GPR) for efficient and accurate radar cross section (RCS) modeling of conducting targets. This study introduces two key innovations. First, we develop an advanced covariance function, termed physical optics-spectral mixture (POSM) covariance function, based on the physical optics (PO) in physics and the spectral mixture method (SMM) in statistics to improve the accuracy and applicability of GPR in modeling the target's RCS. Second, we propose an empirical spectral density-based initialization method for the POSM covariance function, enabling GPR faster converge during training. Experiments conducted with simulated data (involving the NASA almond model, the SLICY model, and a scale-down missile model) and measured data (obtained from the physical model of the missile) demonstrate the superiority of the proposed GPR. It achieves up to an 78.72% reduction in RMSE for simulated data and 69.68% for measured data compared with other alternative covariance function-based GPRs. In terms of efficiency, the training time is reduced by more than 33%, and the well-trained GPR can model the target's RCS in near-real-time (within 0.06 seconds), indicating great potential of our GPR for practical applications in RCS characteristic analysis and data processing like imputation and augmentation. In addition, compared with other alternative machine learning algorithms, such as deep learning (DL), decision tree (DT), and support vector regression (SVR), the proposed POSM-GPR also shows superior precision and respectable efficiency in RCS modeling.

In this letter, a novel inverse design method for metasurfaces (MSs) based on a Wasserstein generative adversarial network with a gradient penalty (WGAN-GP) is presented. Compared with other GAN variants, the proposed WGAN-GP significantly improves the stability and robustness of the training process using the Wasserstein distance and gradient penalty to ensure a smoother optimization landscape. Furthermore, Gramian angular difference fields (GADFs) are introduced to transform electromagnetic (EM) responses into 2-D images. GADFs are characterized by capturing repetitive patterns and structures in a 1D sequence, making them particularly suitable for processing periodic phase data. Therefore, meta-atom patterns and their corresponding EM responses form 2-D input-output pairs, allowing the WGAN-GP to inversely design MSs from an image recognition perspective. As a proof-of-concept example, we experimentally demonstrate a bifunctional MS that integrates second-order orbital angular momentum (OAM) and holographic imaging under dual-linearly polarized excitation. The measured results closely align with the simulated results, thereby validating the feasibility of our inverse design strategy.

In inverse synthetic aperture radar (ISAR) imaging, in order to improve the imaging accuracy at under-sampled conditions, this paper proposes a 2D reweighted l1 norm and Total Variation regularized alternating direction method of multipliers sparse imaging method (2D-RWTV-ADMM). By introducing sparse prior and structure prior, the imaging noise and sidelobes are effectively suppressed, and the target edge information is maintained. The ADMM is adopted to achieve efficient solution, and the dynamic reweighting strategy is combined to enhance the sparse constraint ability. Simulation experimental results show that the proposed method can still maintain good imaging resolution and robustness under undersampled rate and low signal-to-noise ratio conditions, effectively improves the main target focusing ability, suppresses false scattering points, and improves the image edge blurring problem.

This paper introduces an efficient method for the integration of fragmented RCS data using Gaussian process regression (GPR). By leveraging a physics-inspired covariance function derived from the physical optics (PO) approximation, we establish a surrogate model to characterize the frequency-dependent RCS of complex targets. This method enables precise RCS interpolation between the observed frequency bands and extrapolation beyond them. Validation experiments based on the simulated data of the SLICY model and an aircraft model demonstrate small root mean square errors (RMSEs) for both interpolation and extrapolation, less than 0.8 dBsm. Additionally, the proposed method can easily offer the confidence interval (CI) of the predicted result, thus convenient to quantitatively evaluate its reliability.

In this paper, we propose what we believe to be a novel physics and data co-supervised neural network (PaDCoSNN) for estimating the mathematical parameters of a double exponential function based on the physical parameters-rise time and pulse width-of high-altitude electromagnetic pulse (HEMP). Two key structural innovations improve the neural network's estimation accuracy and generalization ability. First, the input (physical parameters) and output (mathematical parameters) layers are structured to reflect their numerical characteristics. Second, nonlinear equations that interpret the relationship between the physical and mathematical parameters are embedded into the loss function to supervise the neural network's learning process. Additionally, a dual-scale probabilistic sampling strategy is proposed to address the issue that uniform sampling in the output space (traditional practice) will result in extremely uneven sample distribution in the input space, thereby generating more representative training samples. Comparative experiments, using 100 sparse training samples and 10000 test samples, demonstrate that PaDCoSNN reduces relative errors by an order of magnitude compared with conventional artificial neural networks (ANNs), with processing times remaining under 1.5 seconds. On out-of-scope test samples, PaDCoSNN demonstrates strong generalization, maintaining relative errors below 0.00001, compared to conventional ANNs, which reach up to 1.7. Moreover, PaDCoSNN has the potential to estimate parameters without sample-based training.

This article presents a novel ultrawideband wide-angle scanning dual-polarized conformal array antenna using the modular concave-down dipole (CDD). The CDD reduces the complexity of the traditional tightly coupled dipole arrays (TCDAs) while maintaining the ultrawideband performance. The shunt capacitance generated by the concave-down structure reduces the active input impedance, which eliminates the need for a complex impedance-matching network and enables direct feeding through a coaxial cable. The mechanisms of generating loop-mode resonance and common-mode resonance in the dual-polarized CDD array are analyzed. A modified tapered coaxial cable loaded with a low-loss ferrite block is proposed to suppress these resonances and achieve wideband operation of the antenna. The profile of the antenna is 0.067 lambda(low) ( lambda(low) is the wavelength at the lowest operating frequency). Leveraging the inherent discontinuity between CDD elements and the compact feed structure, the array is designed in a modular form. Applying the modular approach, a 9x9 dual-polarized CDD array is developed and it is conformally mounted on a cylindrical surface with a radius of 80 mm ( 0.24 lambda(low) ). The proposed antenna is capable of beam scanning of +/- 90 degrees in the conformal plane and +/- 60 degrees in the nonconformal plane within the frequency band of 0.9-5.0 GHz (5.6:1). Besides promising radiation performance, the proposed design uses the modular approach and provides a flexible solution for different platforms including curved platforms.

In this paper, a high switch-isolation (SI) active frequency selective surface (AFSS) design method is proposed. The impedance characteristics of the active resonant structure in frequency domain are studied to provide assistance for enhancing SI. In the non-resonant frequency band, the influence of the slot capacitance during series loading is diminished, and the reconfigurability manifests as a high SI switching characteristic. The designed AFSS exhibits low-pass performance below 10.15 GHz when the PIN diode is turned off, and demonstrates an average SI of 36.9 dB across the switching band.

This paper addresses the challenge of inaccessible phase information in radiation characteristics measurement of integrated wireless devices by proposing a single-scan-plane phaseless antenna characterization method. Existing dual-scanplane phaseless measurement techniques suffer from prolonged measurement durations, high computational complexity, and susceptibility to local minima. To resolve these limitations, the proposed method introduces an auxiliary reference antenna as a phase benchmark. By performing frequency-domain analysis on the measured power spectrum through Fourier transform and integrating a relative phase reconstruction technique between spatial sampling points, this method achieves simultaneous acquisition of electric field amplitude and phase information during a single scanning process. Additionally, the placement optimization of the auxiliary reference antenna is systematically investigated. Experimental results demonstrate the potential of this technique in active integrated antenna measurement systems while revealing critical limitations requiring further optimization, such as undesired reflections caused by interactions between the probe and reference antenna, as well as external environmental interference.

While time-modulated reflectarrays (TMRAs) exhibit flexible beam control capabilities, they often operate at harmonic frequencies, which weakens their practicality. A method is proposed that enables the 1-bit TMRA to achieve beamforming at the carrier frequency. Specifically, four basic control time sequences (BCTSs) are introduced to simultaneously and independently generate an equivalent reflection amplitude-phase distribution, overcoming the limitation of amplitude-only control at the carrier frequency for the 1-bit TMRA. Experimental validation is also conducted, and the results successfully confirm the effectiveness of the proposed method.