Search Results (451)

To address the issue of phase mismatch, mainlobe broadening, image defocusing, and high computational complexity caused by spherical wavefront propagation in near-field imaging of uniform linear array (ULA) imaging sonar, this paper proposes an interpolation-free near-field frequency-domain beamforming algorithm for uniform linear arrays. Under the considered operating conditions, the exact range history is approximated as the sum of a range-dependent quadratic term and a range-independent linear term with respect to the element position. The quadratic term produces negligible envelope migration; therefore, only its phase needs to be compensated. By contrast, the linear term produces more significant range migration, which is corrected together with its associated phase through range-domain and azimuth-domain FFT processing. Under the adopted range-history approximation and discrete sampling conditions, this implementation avoids the explicit point-by-point fractional-delay interpolation required by the backprojection (BP) algorithm. The proposed method substantially reduces the computational cost while maintaining near-field focusing performance comparable to that of the BP algorithm. For the simulated data, the runtime is reduced from 58.23 s to 0.41 s, with only a 0.1% broadening of the azimuth impulse-response width and a 0.11 dB degradation in the peak sidelobe ratio. For the measured lake-trial data, the runtime is reduced from 50.18 s to 0.29 s. Full article

We proposed an all-dielectric stochastically encoded metasurface operating in the 1310 nm near-infrared band, which enables multifunctional optical field manipulation across six independent polarization channels. Utilizing a shared-aperture stochastic matrix-encoding strategy combined with cooperative propagation and geometric-phase decoupling modulation, we investigated stochastically encoded phase distributions, vortex beam profiles, near-diffraction-limited focusing profiles, and the characterization of complex-amplitude multifocal focusing under six independent polarizations. Under left- and right-circularly polarized (LCP/RCP) illumination, vortex beams with topological charges of 1 and 2 have demonstrated substantial enhancement in spatial edge contrast, achieving high edge contrasts of 20 dB and 7.45 dB, respectively, enabling high-fidelity extraction of fine structural boundaries for edge-enhanced imaging. In contrast, near-diffraction-limited focusing under x- and y-polarized illumination has been achieved with numerical apertures (NA) of 0.66 and 0.59, facilitating the realization of bright-field imaging. Significantly, parallel imaging based on complex-amplitude multifocal spot arrays exhibits markedly improved channel isolation, achieving high power ratios of 88.8% and 94.5% under 45° and 135° linearly polarized excitation, respectively. The compact shared-aperture architecture integrates all polarization-controlled functionalities without mechanical tuning, enabling polarization-switchable bright-field imaging, edge detection, and parallel optical manipulation in the near-infrared band. Full article

High-power semiconductor laser diode arrays (LDAs) are pivotal for applications such as optical pumping, industrial manufacturing, and precision measurement, yet they face inherent bottlenecks in balancing high output power, superior beam quality, and stable phase synchronization. The Talbot cavity, leveraging the Talbot self-imaging effect, has emerged as a core external cavity technology to address these challenges, enabling global coupling and passive phase locking of LDAs. This paper systematically reviews the research progress of Talbot cavities in phase-locked LDAs under global coupling. It elaborates on the fundamental principle of Talbot-effect-based phase locking, along with the structural characteristics and working mechanisms of three typical Talbot cavity configurations: conventional Talbot cavities, V-shaped Littrow–Talbot cavities, and monolithic integrated Talbot cavities. Furthermore, it summarizes key experimental advancements of LDAs, covering diverse laser media (e.g., near-infrared, blue, terahertz, and mid-infrared antimonide lasers) and array scales ranging from a few to thousands of emitters, with representative performance metrics including far-field visibility up to 99%, narrowed spectral linewidths achieving 20–50 pm for blue LDA, and output power exceeding 200 W. Numerical simulation progress on supermodel stability and parameter optimization is also discussed. Finally, the current challenges, such as thermal crosstalk and integration complexity, are analyzed, and future prospects involving intelligent control and novel physical mechanisms are outlined. This review aims to provide a comprehensive reference for the further development and practical application of high-brightness phase-locked laser sources. Full article

Metallic blocks and components are indispensable across the aerospace, energy, and heavy-engineering industries, where undetected internal flaws such as cracks, voids, and inclusions may precipitate catastrophic structural failure. Reliable nondestructive evaluation (NDE) is essential to ensure their integrity and operational safety. Among the available NDE techniques, phased array ultrasonic testing (PAUT) has emerged as one of the most accessible and widely adopted, by virtue of its rapid scanning, electronic beam steering, and capacity to image subsurface defects without disassembly. However, the interpretation of PAUT B-scan images remains hindered by background reflections, material-dependent echo characteristics, and substantial variability in defect size. In this work, a fine-tuned encoder–decoder deep learning network is proposed for the automated segmentation of internal defects in PAUT B-scan images of metallic block specimens. The network couples a ResNet50 encoder with a shallow detail stem, a multi-scale feature fusion module, and a detail refinement block, designed to preserve small defect echoes and sharpen weak defect boundaries characteristic of internal flaws. The proposed approach was compared with five state-of-the-art segmentation architectures, namely FCN, PSPNet, DeepLabv3+, HRNet-OCR, and SegFormer, as well as a conventional Otsu-thresholding baseline representing standard PAUT screening practice. Experimental results demonstrate that the proposed network attained the highest Dice score of 0.7964, defect intersection-over-union of 0.6617, and precision of 0.7094 among all evaluated models, while the Otsu baseline yielded the lowest scores, confirming the benefit of learned segmentation over fixed amplitude thresholding. These findings indicate that the proposed network achieves a favorable trade-off between defect localization accuracy and false-positive suppression, underscoring its potential for reliably segmenting internal defects in PAUT B-scan imaging. Full article

Distributed Acoustic Sensing (DAS) provides dense spatial measurements of the dynamic strain along fiber optic cables, offering high-resolution wave sensing for ground motion monitoring and subsurface imaging applications. However, DAS records the axial strain or strain rate, whereas traditional seismic and engineering ground motion equipment and derived metrics are based on particle displacement, velocity, or acceleration, necessitating reliable strain-to-velocity conversion methods. This study evaluates three widely used conversion approaches: the fk-rescaling, curvelet-based conversion, and slant-stack methods. These approaches are applied to a unique high-energy, near-field, active-source dataset collected at the Birds Landing Site in Sherman Island, California. The dataset includes wavefields generated by a large transmission tower collapse and sledgehammer impacts used for subsurface imaging. The wavefields were recorded simultaneously by a 1.4 km DAS array and 71 collocated nodal stations (NSs). Using 63 DAS–NS pairs, we quantify the strain-to-velocity conversion method performance using amplitude and phase transfer functions (TFs) between DAS-derived and NS particle velocity records, with the root-mean-square error (RMSE) evaluated across three frequency bands: 0.5–100 Hz, 1–10 Hz, and 10–100 Hz. The results show that fk-rescaling provides the most stable amplitude response across both source types, while both the fk-rescaling and slant-stack methods generally yield the best phase agreement. Curvelet-based conversion shows a greater variability and larger RMSE values. All methods yield a poorer amplitude reconstruction at higher frequencies, while the phase content is generally preserved more reliably than amplitudes. Differences between the tower collapse and sledgehammer sources demonstrate the influence of the source characteristics and spatial processing window length on the conversion performance. The findings provide practical guidance for selecting suitable strain-to-velocity conversion methods for active-source DAS applications, particularly where collocated reference sensors are unavailable. Full article

The integration requirements of laser ranging, imaging, and communication functions in space target detection have placed higher demands on system performance. This paper takes a modularly designed integrated laser ranging, imaging, and communication system as an example and proposes a light source integration scheme based on fiber phased array beam splitting–coupling technology, effectively enhancing the system’s integration level and compactness. The system employs a Cassegrain optical system and beam splitting structure to achieve functional integration of laser communication, ranging, and polarization imaging. Ground experiments were conducted to evaluate the functional feasibility of the proposed integrated architecture. The visible light polarization imaging experiments at kilometer-level distances demonstrate that polarization-derived information can improve target–background separability under haze and low-contrast conditions. The UAV-based dynamic ranging experiment verifies that the system can acquire, track, and range a moving cooperative target under the tested field conditions, with the measured results being consistent with the designed meter-level ranging requirement. In addition, a 1 km coherent free-space laser communication experiment achieved 20 Gbps QPSK signal transmission with a bit error rate on the order of 10⁻⁷. These results provide experimental support and design references for integrated optoelectronic terminals used in space target observation, space debris monitoring, and related long-distance sensing and communication applications. Full article

In the field of security screening imaging, millimeter-wave technology offers high imaging resolution and low radiation energy. However, it faces challenges such as difficulty in imaging non-cooperative moving targets, as well as bulky equipment and high costs. This paper proposes a high-resolution imaging method based on MIMO millimeter-wave radar. Firstly, the array model and slant range model are established, and a two-dimensional resolution scheme in range and height is constructed using a one-dimensional MIMO linear array and wideband signals. Then, the algorithm flow for MIMO millimeter-wave radar imaging is designed, and a range-domain super-resolution algorithm is introduced. This paper compensates for the phase coupling introduced by the transmitting array and target motion and successfully achieves two-dimensional imaging of non-cooperative targets based on the back-projection principle. Subsequently, the influence of array errors on the imaging results is analyzed. This method compensates for the phase coupling introduced by the transmit array and target motion and provides a theoretical analysis of array arrangement errors. Finally, the experimental results of the MIMO radar are analyzed. The final measured processing results show that the system can clearly reveal metal objects through cloth occlusion, and super-resolution processing yields sharper contours in the imaging of metal plates. Simulation analysis of imaging with array errors indicates that among the azimuth–elevation–range array position errors, the range array position error has a relatively significant impact. Full article

Ultrasound (US) imaging is widely used to guide minimally invasive procedures such as percutaneous nephrolithotomy (PCNL), while electromagnetic (EM) tracking can complement US guidance by providing line-of-sight-independent instrument localization. However, US probes may distort the EM tracking field in a probe-dependent manner. This study characterized probe-induced EM interference for a conventional 3D/4D phased-array probe and a handheld wireless probe. Three experiments were conducted using an EM tracking system: spatial mapping of interference along each probe body, assessment of probe–sensor separation for the handheld probe, and evaluation of probe-induced tracking deviations in a simulated EM-guided PCNL setup with tracked needle and catheter sensors. EM-US calibration was then performed using low-interference sensor positions. The phased-array probe produced minimal disturbance, maintaining submillimetric positional and subdegree orientational precision across tested modes. Compared with the evaluated phased-array probe, the evaluated handheld wireless probe generated stronger, spatially localized interference, requiring ≥75 mm positional and ≥50 mm orientational separation to recover baseline precision. In the PCNL simulation, the phased-array probe maintained tracking stability, whereas the handheld probe introduced localized deviations. Both probes produced RMS calibration residuals below 1 mm under controlled conditions. These results provide device-specific baseline measurements and a workflow for probe-dependent interference assessment and sensor-placement optimization in EM-US navigation. Full article

Wavefront sensing (WFS) is fundamental to adaptive optics, astronomical observation, biological microscopy, and free-space optical communications. However, conventional approaches—including Shack–Hartmann sensors, shearing interferometers, and transport of intensity equation-based methods—are inherently limited by trade-offs among spatial sampling density, angular dynamic range, and device compactness and have rarely been extended to the mid-infrared range. Here, we propose an on-chip mid-infrared wavefront sensing scheme operating based on vectorial photocurrent manipulation and analyze the properties of the proposed device through finite-element simulations. The proposed device comprises a hexagonal array of antenna-integrated graphene pixels, each equipped with three contacts and a microlens. Based on the antenna-induced vectorial photocurrent manipulation, angle-dependent absorption is translated into photocurrent signals, potentially enabling unambiguous recovery of both the elevation and azimuth angles of the incident light over an effective angular dynamic range of ±28°. The hexagonal layout provides a high spatial sampling density of 11,547 mm⁻². Southwell algorithm-based wavefront reconstruction and numerical simulations yield faithful recovery of parabolic, conical, and quadrangular pyramidal wavefronts. In addition, simulation results indicate that this approach can enable high-fidelity reconstruction of both the phase and intensity distributions of an object based on angular-spectrum diffraction theory. Overall, this work theoretically demonstrates a new route toward high-density wavefront measurement and complex light field imaging in the mid-infrared range without a conventional imaging lens. Full article

In airborne sensing applications, radar forward-looking imaging is a crucial technology for high-resolution ground mapping and terrain perception. Super-resolution deconvolution is key to overcoming the real-beam resolution limits of these airborne sensors. However, when utilizing phased array scanning radars for wide-swath ground mapping, the antenna pattern exhibits severe spatial variation at large scanning angles, which directly leads to model mismatch and degradation in super-resolution performance. To address this hardware-induced sensing limitation, this paper proposes a sparse super-resolution method tailored for forward-looking phased array scanning radar. Firstly, the causes of the spatial variation in antenna pattern are analyzed, and a modified antenna convolution matrix is derived to accurately model the scanning process. Secondly, the corresponding objective function is formulated under the assumption of target sparsity. Finally, an alternating direction method of multipliers (ADMM) solver based on reweighted strategy is employed to resolve the objective function. Experimental results demonstrate that the proposed method achieves approximately a 4 times increase in cross-range resolution and effectively enhances the observation capabilities within the radar forward-looking area. Full article

As silicon photonics technology advances toward high-density integration scenarios—such as large-scale matrices, optical phased arrays, and optical neural networks—single-layer waveguide routing encounters severe topological challenges, rendering waveguide crossings indispensable fundamental components for constructing complex on-chip interconnect networks. As photonic hubs bridging distinct functional regions, the insertion loss, crosstalk, and bandwidth of these crossings directly dictate the signal integrity and transmission capacity of optical links. This paper systematically reviews recent research progress and key technologies concerning silicon-based waveguide crossings. Initially, the mechanism of scattering loss in direct crossings is elucidated, followed by a detailed examination of three mainstream design paradigms for loss mitigation: multimode interference (MMI) structures based on the self-imaging principle, adiabatic transformation structures relying on mode evolution, and medium engineering structures utilizing sub-wavelength gratings and metamaterials. Furthermore, the application of algorithm-driven inverse design in overcoming the constraints of traditional physical configurations is discussed. Crucially, addressing the urgent demand for ultra-high transmission capacity in the post-Moore era, this review highlights functional crossings capable of polarization division multiplexing (PDM) and mode division multiplexing (MDM), analyzing the design challenges and breakthroughs associated with multi-dimensional light field manipulation. Finally, this paper presents prospects for the future development trends of the waveguide crossing junction. Full article

Cross-sectional imaging of two-phase oil–water flow in horizontal wells is essential for optimising production, yet conventional deterministic interpolation cannot adapt to varying flow regimes: Kriging smooths chaotic textures while stochastic simulation introduces spurious noise into stable flows. This paper proposes a Flow-Regime-driven Framework for Adaptive Cross-sectional Imaging (FR-FACI) that couples flow-regime identification with image reconstruction. Six physically meaningful features extracted from capacitance (CAT) and turbine (SAT) array signals feed a support vector machine (SVM) classifier that assigns each sampling window to one of three regimes: stratified (SF), stratified-froth (SFF), or froth (FR). A chaos weight derived from the calibrated classifier probability continuously blends detrended ordinary kriging with sequential Gaussian simulation, eliminating hard-switching artefacts. Experiments covering 12 operating conditions yield 95.83% classification accuracy under leave-one-condition-out validation. Variogram ranges differ by more than 26-fold across regimes, confirming the physical necessity of dual-path design. FR-FACI achieves an overall MAE of 0.105 and RMSE of 0.160, matching Kriging in stable flows while recovering chaotic textures that all single-model methods miss. Directions for future work, including uncertainty propagation, field-scale validation, and real-time monitoring integration, are discussed. Full article

Shallow shear-wave velocity structures provide useful constraints on sedimentary architecture in coastal abandoned-estuary settings, yet laterally continuous velocity information remains limited in the Paleo-Yellow River Estuary, Yancheng, Eastern China. In this study, vertical-component ambient noise recorded by a dense linear array of 102 short-period stations over 27 days was used to derive Rayleigh-wave phase-velocity dispersion curves by the modified frequency-Bessel (MFJ) method. Sequential 1D S-wave velocity models were inverted beneath moving subarrays and interpolated to construct a pseudo-2D velocity profile along the survey line. For comparison, the conventional spatial autocorrelation (SPAC) method was applied to the same dataset using the same subarray length, usable frequency band, and inversion-layer parameterization. The MFJ method produces clearer and more concentrated fundamental-mode dispersion energy and suppresses high-frequency crossed artefacts more effectively than SPAC, which improves the stability of dispersion picking. The resulting velocity model reveals a laterally heterogeneous shallow sedimentary system and outlines a U-shaped low-velocity zone that is spatially consistent with the mapped paleochannel boundary. These results indicate that MFJ-based ambient-noise imaging can provide useful complementary geophysical constraints for paleochannel mapping and shallow sedimentary characterization in coastal abandoned-estuary settings. Full article

We propose a terahertz achromatic polarization-multiplexed structured light metasurface based on the particle swarm optimization (PSO) algorithm, operating from 0.8 to 0.95 THz. A dielectric silicon meta-atom array combined with propagation phase modulation is employed to achieve broadband wavefront control under two orthogonal linear polarizations. By constructing a phase-response database and using PSO for global optimization of phase compensation factors at multiple frequencies, the metasurface simultaneously satisfies different target phase profiles while suppressing chromatic aberration. Two multifunctional devices are designed. The first generates a conventional focused spot under x-polarized incidence and a first-order Bessel beam under y-polarized incidence. The second produces a focused vortex beam with topological charge l = 1 under x polarization and a focused vortex beam with l = 2 under y polarization. Full-wave simulations demonstrate stable focal positions, low inter-channel crosstalk, and good achromatic performance across the operating band. The Bessel beam preserves its nondiffracting core, while both vortex channels exhibit clear phase singularities and well-defined orbital angular momentum states. Most operating frequencies maintain relatively high focusing efficiency. Compared with conventional cascaded optical components, our design provides a compact and stable platform for terahertz structured light generation, orbital angular momentum multiplexing, nondiffracting imaging, and multidimensional polarization information processing. Full article

Image demosaicking aims to reconstruct a full-resolution color image from spatially sparse and interleaved color filter array observations. Despite the significant progress achieved by deep learning-based methods, existing approaches have not fully addressed the sampling-structure-constrained nature of demosaicking. In particular, four-channel half-resolution packing may disrupt the CFA spatial phase relationships, while local convolutions and global non-local matching struggle to model reconstruction-relevant cross-position dependencies. To address these issues, this paper proposes an end-to-end image demosaicking network with region-level non-local modeling and residual aggregation (RNRA-Net). Instead of packing Bayer RAW data into a four-channel half-resolution representation, RNRA-Net decomposes the original mosaic image into a three-channel representation at the original resolution, thereby preserving the spatial arrangement of CFA sampling. To capture structurally related information, a region-level non-local module is introduced to compute feature correlations within spatially bounded regions, enabling aggregation of reconstruction-relevant contextual information. In addition, a residual aggregation module is developed to explicitly collect and refine early residual compensation features, facilitating the recovery of edges, textures, and high-frequency details. Extensive experiments on benchmark and high-resolution datasets demonstrate the effectiveness of RNRA-Net. Full article