Search Results (1,071)

Electromagnetic wave manipulation underpins radar detection, imaging, and electronic countermeasures. Conventional phased-array and radio-frequency-chain-based radar architectures provide mature and high-performance operation but can face practical constraints related to aperture profile, power and thermal management, calibration, bandwidth, and multifunctional integration. Electromagnetic metasurfaces provide a complementary approach by controlling the phase, amplitude, polarization, and frequency content of scattered or radiated fields through subwavelength surface elements. This article presents a radar-system-oriented review of metasurface-enabled wave manipulation. We first summarize the relevant physical mechanisms, including generalized scattering, digital and information metasurfaces, time-varying modulation, and polarization and geometric-phase control. We then review experimentally reported applications in radar-cross-section control, programmable beam steering, computational imaging, time-modulated radar, multiple-input multiple-output systems, and integrated sensing and communication. Particular attention is given to the level of experimental validation and to the distinction between measured device- or subsystem-level performance and anticipated system-level benefits. Potential applications in stealth, radar deception, low-probability-of-intercept-oriented operation, and cognitive sensing are discussed together with limitations in bandwidth, efficiency, power handling, biasing, calibration, thermal management, and scalability. Overall, the available literature indicates that metasurfaces can support selected aperture-level radar functions, whereas general system-level advantages in SWaP, cost, latency, and energy efficiency remain to be established through controlled comparative experiments. Full article

The ground-airborne frequency-domain electromagnetic (GAFEM) method has the potential to detect underground anomalies at large depth ranges in areas with complex terrain. However, its specific configuration, which involves ground-based transmitting and airborne signal acquisition, inevitably introduces attitude noise into the measured magnetic field vector data. The presence of this attitude noise alters the characteristics of the measured data, consequently compromising the accuracy of imaging methods that rely on vector data. To eliminate the influence of attitude on GAFEM, this study proposes a rapid imaging technique for GAFEM based on the scalar magnetic field. This method utilizes the total magnetic field magnitude at each measurement point along the survey line as the input for imaging parameter calculation, thereby circumventing the effects of attitude noise and enabling high-resolution detection of underground anomalies. This study begins by analyzing the mechanism through which flight attitude affects GAFEM. Using a previously published GAFEM imaging method based on vector magnetic fields, it is demonstrated that flight attitude severely degrades the accuracy of such methods. Furthermore, a new imaging approach is proposed that employs the scalar magnetic field, which is immune to variations in flight attitude. A detailed description of the method’s principles, physical basis, and computational procedures is provided. The feasibility of the method is validated using a synthetic GAFEM model. The results indicate that the proposed method can achieve high-resolution detection of underground anomalies without being affected by attitude noise. Finally, the performance of the method is further tested using a simulation model constructed from actual geological data. The results confirm that the proposed method possesses the capability to identify underground anomalies in a complex model. Full article

This paper presents a DSM-initialized U-Net framework for reconstructing the shape of a perfectly conducting target buried in a slab medium from measured electromagnetic scattered fields. The conductive target is irradiated with Transverse Electric (TE) waves, followed by the acquisition of the resulting scattered fields. These scattered field data were first used for forward scattering calculations with the Method of Moments (MoM), followed by preliminary shape reconstruction using the DSM. The preliminary images received from the DSM were then input into a U-Net for imaging. Compared with the free space case, the slab medium condition limited the incident and receiving angles. Numerical results indicate that the standalone DSM provides only an approximate estimate of the conductor profile, whereas the proposed DSM–U-Net framework achieves average NRMSE values of 6.90% under 5% Gaussian noise and 8.95% when trained with 5% noise and tested with 10% noise. Full article

A Spiking Neural Network (SNN) is a kind of brain-inspired and event-driven network, which is becoming a promising energy-efficient alternative to Artificial Neural Networks (ANNs). In recent years, SNN methods have been successfully applied in the fields of electromagnetic signal processing and image signal processing, particularly in application scenarios that require low energy consumption. However, the performance of SNNs by direct training is far from satisfactory. In this paper, we study a novel learning method named SAD-SNN (Spatial-Activation Distillation for Spiking Neural Networks), which utilizes the ANN model to guide the SNN model learning. Unlike prior works that rely on element-wise feature alignment approaches, SAD-SNN aligns spatial-activation maps at different resolutions of the teacher and student networks. Specifically, we introduce a direct alignment approach, which defines a spatial-activation loss and normalizes the representation vectors of ANN and SNN, to alleviate the unexpected precision loss. This enables the knowledge of teacher ANNs to be effectively transferred to train student SNNs. On three image classification datasets, our proposed SAD-SNN outperforms other SNN training methods no matter whether homogeneous or heterogeneous teacher ANNs are used. Furthermore, we apply SAD-SNN to the electromagnetic signal detection task, demonstrating strong generalization ability and superior performance. In conclusion, the experimental results on various tasks and SNN architectures demonstrate that our method is a general and effective solution that significantly improves the learning of student SNNs with only two time steps. Full article

Termite infestation poses a critical threat to ancient timber structures because hidden in-wood activity can cause progressive structural decay before visible surface symptoms appear. Through-wood termite detection remains challenging because termite-induced electromagnetic responses are weak, small-scale, and vulnerable to timber attenuation and multipath propagation. To address this problem, this study presents one of the first investigations to formulate through-wood termite detection as a multi-frequency wireless sensing and image–wireless fusion problem for non-destructive heritage timber inspection. We propose a Reliability-Aware Image–Wireless Fusion Network (RA-IWFNet), in which the image branch captures high-resolution surface-level visual cues while the dual-band wireless branch integrates complementary mmWave radar micro-motion responses and Wi-Fi Channel State Information (CSI) channel variations. A learnable temperature-scaled fusion gate estimates input-dependent image and wireless contributions and constructs a normalized fused representation for four-class recognition, including Termite, Lyctidae, Human, and None. Here, reliability is operationally defined as learned input-adaptive relative modality contribution rather than explicit uncertainty or signal-quality estimation. RA-IWFNet is evaluated under two complementary protocols: a field-motivated protocol with joint visual and wireless degradation and a synchronized verification protocol using physically co-acquired multimodal samples. Across repeated training runs, RA-IWFNet achieves $81.91\pm 1.33\%$ accuracy and $81.96\pm 1.27\%$ Macro-F1 under field-mixed visual degradation and moderate wireless degradation. On the synchronized verification subset, gated fusion achieves $91.53\pm 2.44\%$ accuracy and $91.62\pm 2.44\%$ Macro-F1, yielding higher mean performance than single-modality and non-adaptive fusion baselines. Feature-space, error-correction, and gate-temperature analyses further support the effectiveness of adaptive modality integration. These results provide controlled laboratory feasibility evidence and suggest that multi-frequency wireless sensing combined with adaptive image–wireless fusion offers a promising non-invasive pathway toward practical through-wood termite inspection in heritage timber structures. Full article

Stress–strain detection serves as a common inspection technique in engineering integrity management, enabling the prediction of the health status and remaining service life of materials or structures. This study systematically investigates the performance and application effectiveness of Digital Image Correlation (DIC) and Alternating Current Stress Measurement (ACSM) technologies in the field of stress–strain detection. Based on the inverse magnetostriction effect and Maxwell’s equations, an ACSM detection system was developed, achieving the conversion of stress signals into electromagnetic signals. Simultaneously, DIC technology combined with a high-resolution binocular vision system was employed to realize non-contact measurement of full-field strain distribution. Finite element analysis using COMSOL V6.1 software was conducted to simulate the stress–strain distribution of ferrous specimens under axial tensile load, identifying the range of the gauge section with uniform stress–strain distribution. An experimental platform was established to perform tensile tests on flat specimens. The results demonstrated that the stress detection error of the ACSM system was less than 42.93 MPa, the strain measurement error of the DIC system was below 2.14722 × 10⁻⁴, and the stress inversion error was less than 31 MPa. A comprehensive comparison indicates that DIC technology offers superior performance in measurement accuracy and resolution, while ACSM technology provides advantages in operational convenience and rapid response, making it suitable for rapid screening in industrial settings. Full article

The short-offset transient electromagnetic method (SOTEM) has become a popular research topic in recent years. In this paper, we present the vector finite element method based on model reduction, which greatly improves computational efficiency. Based on the Krylov subspace projection method, the electromagnetic response of multi-frequency is quickly obtained using model reduction, and the acceleration ratio reaches 33. The electromagnetic field in the time domain is obtained using cosine transformation. A translation algorithm is used to calculate the full-time apparent resistivity. The correctness of the algorithm is verified using uniform half-space model and a complex geoelectric model. Then the amplitude of the transient electromagnetic apparent resistivity anomaly of the 1D, 2D, and 3D geoelectric models is compared. Results show that the electromagnetic response amplitude from the 1D model is much greater than the ones from the 2D and 3D models. Special attention needs to be paid to the processing and interpreting field data using the 1D forward and inversion method. Additionally, we analyze the impulse responses at the different offsets for the conductive body, and the results indicate that with the decrease in the offset, the impulse response and anomalous amplitude are greatly enhanced, and exploration depth and resolution are also improved. The porphyry Cu-Mo deposit model experiment further demonstrates that three-dimensional SOTEM forward modeling combined with full-time apparent resistivity imaging can effectively identify low-resistivity mineralized anomalies within a complex geological model at depths of approximately 200–500 m, thereby confirming the applicability of the method to realistic mineral deposit exploration. Full article

With the accelerated advancement of smart city construction, the development of urban underground space in coastal areas faces significant safety challenges due to randomly distributed granite boulders. Conventional geophysical methods often struggle to identify these heterogeneous bodies efficiently. This study proposes a comprehensive detection approach fusing the Cone-based Transient Electromagnetic Method (CTEM) and Microtremor Array Surveying. Taking the eastern coast of Jiaozhou Bay, Qingdao, as the research area, we integrated borehole data to validate the geophysical interpretation. The results demonstrate that the joint inversion accurately delineates four stratigraphic interfaces with depths consistent with borehole logs: the artificial fill (bottom at ~8–12 m), Quaternary sediments (~28–33 m), strongly weathered granite (~59–74 m), and moderately weathered granite. Specifically, boulders within the Quaternary and strongly weathered layers are distinctly identified by dual high-value anomalies: high apparent resistivity (>220 Ωm, approximately 1.5–2 times that of the surrounding rock) and high shear-wave velocity (>660 m/s). Furthermore, the method effectively differentiates boulders from water-rich fractured zones, which exhibit contrasting low resistivity (<50 Ωm) and low shear-wave velocity (<420 m/s). These quantitative findings confirm that the fused CTEM and microtremor technique provides precise spatial localization and reliable identification of boulders in complex coastal geological environments. Full article

Seawater intrusion poses a major threat to groundwater quality in the Al-Batinah Coastal Plain of northern Oman, where intensive groundwater abstraction has disrupted the natural freshwater–seawater equilibrium in the coastal alluvial aquifer. This study investigates the extent and geometry of seawater intrusion in the eastern sector of the aquifer, between Al-Jifnain Dam and the Oman Sea, using the transient electromagnetic (TEM) method. A total of 45 TEM soundings were acquired along four profiles and inverted using a laterally constrained inversion (LCI) scheme to recover spatially coherent subsurface resistivity models. The results resolve the principal hydrostratigraphic units of the coastal aquifer system, including a highly resistive unsaturated near-surface gravel cover, a moderately resistive freshwater-bearing gravel aquifer, and localized conductive horizons interpreted as clay-rich gravel interbeds. The most prominent feature is a laterally extensive wedge-shaped conductive body, with resistivities close to 1 Ω·m, extending inland beneath the freshwater aquifer and interpreted as seawater intrusion. This saline wedge extends approximately 8 km inland from the coast, between elevations of about −70 and −220 m, with maximum thickness near the shoreline and progressive thinning landward. The study demonstrates that TEM, combined with LCI, is an effective approach for delineating deep seawater intrusion in arid coastal aquifers and provides a baseline for future monitoring of aquifer salinization and for assessing the impact of managed aquifer recharge in the Al-Jifnain area. These findings support sustainable groundwater management and contribute to achieving the United Nations Sustainable Development Goal 6 (Clean Water and Sanitation). Full article

Exploration of the Gaolihan (GLH) Sag in the Erlian Basin remains low due to the discontinuity of early-stage 2D seismic surveys that have failed to provide regional coverage, leaving the deep geological framework unclear and hindering hydrocarbon breakthroughs. To address this problem and to evaluate the resource potential of the pre-Cretaceous formation, this study applied an integrated geophysical workflow combining 1:50,000 high-precision gravity–magnetic surveys, gravity–magnetic well–seismic joining in the forward and inversion directions, layer stripping, and time–frequency electromagnetic method (TFEM) profiling. Using logging resistivity curves from wells GC1 and LT1 for electrical calibration, we delineated the fault system, stratigraphic framework, and deep lithology of the GLH Sag. The key results include the following: (1) identification of 12 faults defining a “three sags and three uplifts” structural pattern; (2) burial depths of the Cretaceous, Jurassic, and Carboniferous–Permian basements ranging from 3000 to 3300 m, 4400 to 4600 m, and 6500 to 6700 m, respectively; and (3) recognition of three electrical layers within the Jurassic, with high-resistivity intervals indicating basalt and low-resistivity intervals interpreted as coal-bearing formation of the Lower Jurassic Hongqi formation. Quantitative validation against wells GC1 and LT1 demonstrates that the TFEM-inverted resistivity values show an average absolute deviation of ~2.5 Ω·m from measured logs (relative error <12% for resistivities >5 Ω·m), with an overall stratigraphic boundary consistency exceeding 85%. Lithologic prediction accuracies reach 88% for sandstone/siltstone and 82% for mudstone/carbonaceous mudstone. This integrated workflow proves effective for deep structural imaging and lithology prediction in volcanic-covered, seismically poor areas, and provides a practical reference for similar low-exploration basins. Full article

Background: Accurate thyroid volume measurement is essential for diagnosing and monitoring thyroid disorders and for determining radioiodine therapy dosage. The ellipsoid method applied to two-dimensional B-mode ultrasound (Bmode-2D-US) is the most prevalent clinical approach, yet it is known to suffer from high observer dependence and limited accuracy. Tracked three-dimensional ultrasound (3D-US) is a promising radiation-free alternative, but direct comparisons across modalities under controlled conditions remain scarce. Methods: A custom-built anthropomorphic multi-modality phantom was constructed containing six anatomically realistic thyroid lobe samples molded from segmented MRI data, with ground truth volumes verified by the suspension method and 3D surface scanning. Volume measurements were performed by six observers of varying experience using Bmode-2D-US, electromagnetically tracked 3D-US (EM-3D-US), inertial-measurement-unit-tracked 3D-US (IMU-3D-US), and optically tracked 3D-US (Opt-3D-US), as well as computed tomography (CT) and magnetic resonance imaging (MRI). Inter- and intraobserver variability were assessed using modified Bland–Altman analysis. Results: All three 3D-US methods reduced inter- and intraobserver variability compared to Bmode-2D-US, achieving variability comparable to CT and lower than MRI. Mean accuracy was similar across 3D-US, CT, and MRI. Bmode-2D-US showed strong observer dependence, with operator experience having the most pronounced effect on this method. Among tracked methods, EM-3D-US and Opt-3D-US were least sensitive to operator movement quality, while IMU-3D-US showed somewhat higher sensitivity. Conclusions: Tracked 3D-US is a promising radiation-free alternative to conventional Bmode-2D-US for thyroid volumetry, offering improved reproducibility and accuracy across operators of varying experience in this phantom-based evaluation. Full article

Accurate monitoring of temperature variations in fluid flow through porous media is important for numerous geophysical, environmental, and chemical processes. Traditional temperature measurement techniques often suffer from limitations such as invasiveness, restricted spatial coverage, or limited capability for real-time subsurface sensing. Thermoacoustic (TA) methods provide a promising alternative by combining electromagnetic excitation with acoustic detection to enable non-contact subsurface monitoring. In this work, thermoacoustic measurements were conducted over a temperature range of 20–60 °C using a water-saturated sand porous medium, and a multiphysics simulation framework incorporating rock physics models, temperature-dependent material properties, acoustic dispersion, and attenuation calibration was developed to reproduce the experimental observations. A clear relationship between temperature and TA signal amplitude was observed, and strong agreement was achieved between the experimentally measured and simulated thermoacoustic responses after applying the proposed calibration procedures. The results demonstrate the feasibility of using thermoacoustic signals to monitor bulk temperature variations in porous media and establish a foundation for future development of spatially resolved thermoacoustic temperature imaging methods. Full article

Multidimensional metasurfaces provide a promising platform for terahertz (THz) multifunctional devices used in communication, imaging, and sensing. However, many THz multifunctional devices still rely on metallic or periodic metasurfaces, which may suffer from ohmic loss, unwanted diffraction, channel crosstalk, and energy leakage. To address these limitations, we propose an all-dielectric THz metasurface based on a five-fold rotationally symmetric quasicrystalline aperiodic tiling and verify its performance through full-wave electromagnetic simulations. High-resistivity silicon rectangular pillars are used as anisotropic propagation-phase meta-atoms, enabling independent wavefront encoding for two orthogonal linear polarizations within a single aperture. By mapping the x- and y-polarized phase profiles onto the quasicrystalline lattice, the proposed device realizes polarization-multiplexed bifocal focusing with controllable focal positions. Simulation results show high focusing efficiency, low polarization crosstalk, broadband focusing performance, and robustness under oblique incidence. This work provides a compact all-dielectric route for multifunctional THz wavefront control based on polarization multiplexing and quasicrystalline metasurface design. Full article

Stochastic radiation radar (SRR) utilizes stochastic electromagnetic wave signals to form a radiation field randomly distributed in space, offering advantages such as non-reliance on motion for high resolution imaging. However, existing SRRs typically acquire batched data through long-duration staring observations of the target, followed by target reconstruction to obtain high-resolution imaging results, leading to low imaging efficiency. Depending on the data acquisition mode of the stochastic radiation radar, this paper proposes a Progressive Staring Sparse Pruning (PSSP) Approach. On the one hand, a staring sparse pruning framework is proposed to construct an active set of target grids, which utilizes the structural feasibility gate and incremental significance characteristic of the closed-form solution. On the other hand, an adaptive progressive termination criterion is established to reduce computational complexity, which adopts an adaptive relative-coefficient criterion and a progressive active-set-size criterion to avoid focusing only on a few repeatedly active grids and to reduce unnecessary echo-sample processing. Simulation results demonstrate that the proposed method fully exploits the advantages of stochastic radiation radar staring observation, substantially improving computational efficiency while guaranteeing imaging performance. Full article

Conventional Pancharatnam–Berry (PB) phase metasurfaces operate within the two-dimensional SU(2) polarization space of the electric field, fundamentally limiting holographic multiplexing to two independent channels. Here, we propose and numerically demonstrate a four-channel holographic metasurface exploiting the recently discovered Riemann–Silberstein (RS) geometric phase arising from SU(4) polarization evolution in the full electromagnetic field space. The RS vector Ψ = E + icB unifies electric and magnetic fields into a four-dimensional polarization state space. By engineering bianisotropic Huygens meta-atoms with independently controllable electric-dipole orientation angle α and magnetic-dipole orientation angle ψ, four geometric-phase channels—labeled by the joint spin eigenstates |σ,κ⟩∈{|+,+⟩,|+,−⟩,|−,+⟩,|−,−⟩}—are simultaneously addressed from a single aperture. We develop the complete SU(4) transfer-matrix formalism and optimize four quasi-independent phase profiles using an extended Gerchberg–Saxton algorithm with a three-parameter (α,ψ,h) design library, where the pillar height h serves as a third degree of freedom to overcome the linear phase constraint inherent to the two-angle parameterization. Numerical simulations at 0.8 THz demonstrate simultaneous projection of four independent holographic images with mean diffraction efficiency 60.4% and inter-channel crosstalk below 3.2%, doubling the information capacity of conventional dual-channel PB holograms. An intrinsic ~24× common-mode noise suppression arising from electromagnetic duality symmetry is also demonstrated. This work establishes a direct link between fundamental electromagnetic symmetry and high-capacity wavefront engineering. Full article