Search Results (432)

Continuous, single-mode imaging systems fail to deliver true-color high-resolution imagery around the clock under extreme lighting. High-fidelity color and signal-to-noise ratio imaging across the full day–night cycle remains a critical challenge for surveillance, navigation, and environmental monitoring. We present a competitive dual-mode imaging platform that integrates a 155 mm f/6 telephoto daytime camera with a 52 mm f/1.5 large-aperture low-light full-color night-vision camera into a single, co-registered 26 cm housing. By employing a sixth-order aspheric surface to reduce the element count and weight, our system achieves near-diffraction-limited MTF (>0.5 at 90.9 lp/mm) in daylight and sub-pixel RMS blur < 7 μm at 38.5 lp/mm under low-light conditions. Field validation at 0.0009 lux confirms high-SNR, full-color capture from bright noon to the darkest nights, enabling seamless switching between long-range, high-resolution surveillance and sensitive, low-light color imaging. This compact, robust design promises to elevate applications in security monitoring, autonomous navigation, wildlife observation, and disaster response by providing uninterrupted, color-faithful vision in all lighting regimes. Full article

Azimuth ambiguity caused by spectral aliasing severely degrades the quality of Synthetic Aperture Radar (SAR) images. To suppress azimuth ambiguity while preserving image details as much as possible, this paper proposes an azimuth ambiguity suppression method for SAR based on time-frequency joint analysis. By exploiting the distribution differences of ambiguous signals across different sub-spectra, the method locates azimuth ambiguity in the time domain through multi-sub-spectrum change detection and fusion, followed by ambiguity suppression in the azimuth time-frequency domain. Experimental results demonstrate that the proposed method effectively suppresses azimuth ambiguity while maintaining superior performance in preserving genuine targets. Full article

Real-time Synthetic Aperture Radar (SAR) imaging for small Unmanned Aerial Vehicles (UAVs) has become a significant research focus. However, limitations in Size, Weight, and Power (SwaP) restrict the imaging quality and timeliness of small UAV-borne SAR, limiting its practical application. This paper presents a non-iterative real-time Feature Sub-image Based Stripmap Phase Gradient Autofocus (FSI-SPGA) algorithm. The FSI-SPGA algorithm combines 2D Constant False Alarm Rate (CFAR) for coarse point selection and spatial decorrelation for refined point selection. This approach enables the accurate extraction of high-quality scattering points. Using these points, the algorithm constructs a feature sub-image containing comprehensive phase error information and performs a non-iterative phase error estimation based on this sub-image. To address the multifunctional, low-power, and real-time requirements of small UAV SAR, we designed a highly efficient hybrid architecture. This architecture integrates dataflow reconfigurability and dynamic partial reconfiguration and is based on an ARM + FPGA platform. It is specifically tailored to the computational characteristics of the FSI-SPGA algorithm. The proposed scheme was assessed using data from a 6 kg small SAR system equipped with centimeter-level INS/GPS. For SAR images of size 4096 × 12,288, the FSI-SPGA algorithm demonstrated a 6 times improvement in processing efficiency compared to traditional methods while maintaining the same level of precision. The high-efficiency reconfigurable ARM + FPGA architecture processed the algorithm in 6.02 s, achieving 12 times the processing speed and three times the energy efficiency of a single low-power ARM platform. These results confirm the effectiveness of the proposed solution for enabling high-quality real-time SAR imaging under stringent SwaP constraints. Full article

The continuous progress of synthetic aperture radar (SAR) imaging has led to a growing emphasis on the challenges involved in data acquisition and processing. And the challenges in data acquisition and processing have become increasingly prominent. However, traditional SAR imaging models are limited by their large demand for data sampling and slow image reconstruction speeds, which is particularly prominent in large-scale scene applications. To overcome these limitations, this study proposes an innovative L₁-Total Variation (TV) regularization sparse SAR imaging algorithm. The submitted algorithm constructs an imaging operator and an echo simulation operator to achieve decoupling in the azimuth and range dimensions, respectively, as well as to reduce the requirement for sampling data. In addition, a Newton acceleration iterative method is introduced to the optimization process, aiming to accelerate the speed of image reconstruction. Comparative analysis and experimental validation indicate that the proposed sparse SAR imaging algorithm outperforms conventional methods in resolution, target localization, and clutter suppression. The results suggest strong potential for rapid scene reconstruction and real-time monitoring in complex environments. Full article

Synthetic aperture radar (SAR) automatic target recognition (ATR) plays a pivotal role in SAR image interpretation. While existing approaches predominantly rely on batch learning paradigms, their practical deployment is constrained by the sequential arrival of training data and high retraining costs. To overcome this challenge, this paper introduces a divergence-constrained incremental dictionary learning framework that enables progressive model updates without full data reprocessing. Specifically, firstly, this method learns class-specific dictionaries for each target category via sub-dictionary learning, where the learning process for a specific class does not involve data from other classes. Secondly, the intra-class divergence constraint is incorporated during sub-dictionary learning to address the challenges of significant intra-class variations and minor inter-class differences in SAR targets. Thirdly, the sparse representation coefficients of the target to be classified are solved across all sub-dictionaries, followed by the computation of corresponding reconstruction errors and intra-class divergence metrics to achieve classification. Finally, when the targets of new categories are obtained, the corresponding class-specific dictionaries are calculated and added to the learned dictionary set. In this way, the incremental update of the SAR ATR system is completed. Experimental results on the MSTAR dataset indicate that our method attains >96.62% accuracy across various incremental scenarios. Compared with other state-of-the-art methods, it demonstrates better recognition performance and robustness. Full article

High-gradient accelerating radio frequency (RF) ] cavities are currently being developed in several national laboratories for applications in high-energy physics. Ultra-high accelerating gradients, reaching up to the GV/m range, can be achieved using ultra-compact accelerating structures operating in the sub-terahertz (sub-THz) regime. However, accurately measuring the key RF parameters of such compact structures presents significant experimental challenges, and even minor inaccuracies can lead to substantial errors. Additionally, RF simulations for these cavities often require extensive computational resources. Among the most critical parameters to determine is the reflection coefficient. To provide a fast and accurate analytical estimation, we have developed an electromagnetic theory describing the coupling between a resonant cavity and an RF waveguide. This approach is based on Bethe’s small-aperture polarization method, further developed by Collin. An exact analytical expression for the reflection coefficient is presented, formulated as a function of the physical parameters of the cavity waveguide system and applicable to arbitrary geometries, materials, and frequencies. Full article

In this paper, a wideband circularly polarized folded reflectarray antenna (CPFRA) based on a transmissive linear-to-circular polarization converter is proposed. The CPFRA consists of a primary reflector and a sub-reflector. To achieve broadband performance, a metasurface-based RA element on the primary reflector surface and a transmissive linear-to-circular polarization converter on the sub-reflector surface are applied. Moreover, the transmissive linear-to-circular polarization converter on the sub-reflector surface helps convert linear polarization to circular polarization. To verify the proposed CPFRA, a prototype is designed, fabricated, and tested. The measured results exhibit that the proposed CPFRA presents a 3 dB gain bandwidth of 27.4% and a 3 dB axial ratio bandwidth of 23%. The CPFRA achieves a peak gain of 21.2 dBi with an aperture efficiency of 27.2%. The proposed CPFRA is a promising candidate for millimeter-wave (mm-W) satellite communication applications because of its advantages of high gain, low cost, low profile, and broad bandwidth. Full article

The generation and propagation mechanisms of acoustic waves from leakage below the annular liquid level in gas wells have attracted widespread attention. To study the characteristics of acoustic sources beneath the liquid level, a physical model of leakage in the casing–tubing annulus was established by simulating the distribution patterns of the flow field and acoustic field within the annulus under tubing leakage conditions. Distinct from the traditional acoustic analysis of wellbore leakage in gas wells, this study focuses on acoustic waves generated by leaks located below the annular protection fluid level. It analyzes the flow regime and acoustic source characteristics beneath the liquid level under various operating conditions (including leakage aperture, velocity, and position). The research summarizes the evolution patterns of flow regimes when gas leaks into the annular protection fluid under different conditions and elucidates the generation mechanism of sub-liquid leakage noise and its propagation mechanism across the liquid surface. This work lays the theoretical foundation for detecting sub-liquid leakage at the wellhead using acoustic methods. Full article

Synthetic aperture radar (SAR) is an all-weather and all-day imaging technique for Earth observation. Achieving efficient observation, high resolution, and wide swath coverage have remained critical development goals in SAR technology, which inherently require extended synthetic aperture time. However, various non-ideal factors, including atmospheric disturbances, orbital perturbations, and antenna vibrations. degrade imaging performance, causing defocusing and ghost targets. Furthermore, the long synthetic time and large imaging swath further enlarge the temporal and spatial variability of these factors and seriously degrade the imaging effect. These inherent challenges make autofocusing indispensable for SAR imaging with a long synthetic time and large swath. In this paper, a novel autofocus method specifically designed to address these non-ideal factors is proposed for SAR imaging with a long synthetic time and large swath. The innovation of the method mainly consists of two parts. The first is the autofocus for multiple non-ideal factors, which is accomplished by an improved phase gradient autofocus (PGA) equipped with amplitude error estimation and discrete windowing. PGA with amplitude error estimation can solve the problem of defocus, and discrete windowing can focus the energy of paired echoes. The second is an error fusion and interpolation method for a long synthetic time and large swath. This method fuses errors among sub-apertures in the long synthetic time and can fulfill autofocus for blocks where strong scatterers are not sufficient in the large swath. The proposed method can effectively achieve SAR focusing with a long synthetic time and large swath, considering spatial and temporal variant non-ideal factors. Point target simulations and distributed target simulations based on real scenarios are conducted to validate the proposed method. Full article

Rapid urbanization has transformed cityscapes worldwide, yet vertical urban growth (VUG) receives less attention than horizontal expansion. This study mapped and analyzed VUG patterns in Wuhan, China, from 2012 to 2020 based on a Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) dataset derived from a long time series of 375 COSMO-SkyMed SAR images. The methodology involved full-stack processing (analyzing all 375 images for a stable reference), sub-stack processing (independently processing sequential image subsets to track temporal changes), and post-processing to extract persistent scatterer (PS) candidates, estimate building heights, and analyze temporal changes. Validation was conducted through drone surveys and ground measurements in the Hanyang district. Results revealed substantial vertical expansion in central districts, with Hanyang experiencing a 66-fold increase in areas with buildings exceeding 90 m in height, while Hongshan district saw a 34-fold increase. Peripheral districts instead displayed more modest growth. Time series analysis and 3D visualization captured VUG temporal dynamics, identifying specific rapidly transforming urban sectors within Hanyang. Although the study is focused on one city with accuracy assessed on a spatially confined sample of more than 500 buildings, the findings suggest that PSInSAR height estimates from high-resolution SAR imagery can complement global settlement datasets (e.g., Global Human Settlement Layer, GHSL) in order to achieve better accuracy for individual building heights. Validation generally confirmed the accuracy of PSInSAR-derived height estimates, though challenges remain with noise and the distribution of PS. The location of PS along the building instead of the building rooftops can affect height estimation precision. Full article

Phosphogypsum leachate significantly accelerates carbonate rock dissolution in karst regions. The dissolution mechanism of phosphogypsum leachate associated with carbonate rock interaction and the corresponding numerical simulation need further study. In this study, 3D digital core imaging was used to scan undisturbed carbonate rock specimens from phosphogypsum landfill sites, and corresponding 3D structural models were constructed. We carried out indoor dissolution experiments in which we used Scanning Electron Microscopy as well as Energy Dispersive Spectrometer to observe changes in the surface micromorphology and elemental content of the rock specimens under different dissolution conditions. A reactive numerical model was developed based on the 3D structural model obtained from 3D digital core imaging, and numerical simulation studies were conducted. The dissolution reaction between phosphogypsum leachate and carbonate rocks exhibited an initial rapid phase followed by gradual stabilization. The pH of the leachate showed an exponential negative correlation with the dissolution amount per unit area of the rock specimens, while a power-law negative correlation was observed between pH and chemical dissolution rates. The numerical model effectively reproduced the reactant concentration states observed in experiments, confirming its capability to simulate reaction processes within rock specimens. Simulation results demonstrated that preferential flow through fracture channels led to higher reactant concentrations near fractures due to incomplete reactions, whereas lower concentrations occurred in sub-fracture regions. As the fracture aperture increased, the concentration disparity between these regions became more pronounced, with higher concentration of reactants at the outlet. Full article

As a special component, inner-wall-shaped parts with a narrow aperture and large cavity play an important role in the field of industrial manufacturing. It is of great significance to accurately measure the full profile of the inner surface of such parts. Line-structured light scanning is a widely used method for inner wall 3D measurement, which is usually applied to linear scanning measurements of the inner wall of pipe-shaped parts. In view of the structural characteristics of narrow-aperture and large-cavity parts, this article establishes a multi-sensor scanning measurement system based on the principle of line-structured light, which adopts rotary scanning instead of the traditional linear scanning measurement method in the system. Additionally, a calibration method is introduced to resolve the challenges associated with the calibration of rotation axis parameters. Considering the structural constraints in the measurement of narrow-aperture and large-cavity parts, a structural optimization algorithm is designed to enable the sensor to achieve a high theoretical measurement resolution while satisfying the geometric constraints of the measured parts. In order to minimize the size of the sensor, the adjacent sub-sensors in the system are arranged in the form of low overlapping fields of view (FOV). To solve the problem of multi-sensor registration under low overlapping FOV, a calibration method based on the structural characteristics of the measurement system itself is proposed, which realizes low-cost and high-precision calibration of the multi-sensor system. Through the repeatability measurement experiment of the spherical cavity parts, the average measurement deviation of the spherical cavity radius was measured to be 6 μm, and the standard deviation was 11.4 μm, which verified the feasibility of the measurement system proposed in this article. By comparing the system calibration method proposed in this article with existing methods, the measurement accuracy of the system is improved by approximately 80%, demonstrating the effectiveness of the proposed method. Full article

Permanent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR), with millimeter-level accuracy and full-resolution capabilities, is essential for monitoring urban deformation. With the advancement of SAR sensors in spatial and temporal resolution and the expansion of wide-swath observation capabilities, the number of permanent scatterers (PSs) in high-density urban areas has surged exponentially. To address these computational and memory challenges in high-density urban PSInSAR processing, this paper proposes an efficient method for integrating regular grid partitioning and connected component constraints. First, adaptive dynamic regular grid partitioning was employed to divide monitoring areas into sub-blocks, balancing memory usage and computational efficiency. Second, a weighted least squares adjustment model using common PS points in overlapping regions eliminated systematic inter-sub-block biases, ensuring global consistency. A graph-based connected component constraint mechanism was introduced to resolve multi-component segmentation issues within sub-blocks to preserve discontinuous PS information. Experiments on TerraSAR-X data covering Fuzhou, China (590 km²), demonstrated that the method processed 1.4 × 10⁷ PS points under 32 GB memory constraints, where it achieved a 25-fold efficiency improvement over traditional global PSInSAR. The deformation rates and elevation residuals exhibited high consistency with conventional methods (correlation coefficient ≥ 0.98). This method effectively addresses the issues of memory overflow, connectivity loss between sub-blocks, and cumulative merging errors in large-scale PS networks. It provides an efficient solution for wide-area millimeter-scale deformation monitoring in high-density urban areas, supporting applications such as geohazard early warning and urban infrastructure safety assessment. Full article

Ship wake detection plays a crucial role in compensating for target detection failures caused by defocusing or displacement in SAR images due to vessel motion. This study addresses the challenge of enhancing wake features in high-resolution spaceborne SAR by exploiting the distinct linear characteristics of wake echoes and the random motion of ocean background clutter. We propose a novel method based on sub-aperture image sequences, which integrates equivalent multi-channel technology to fuse wake and wave information. This approach significantly improves the quality of raw wake images by enhancing linear features and suppressing background noise. The Radon transform is then applied to evaluate the enhanced wake images. Through a combination of principle analysis, enhancement processing, and both subjective and objective evaluations, we conducted experiments using real data from the AS01 SAR satellite and compared our method with traditional wake enhancement techniques. The results demonstrate that our method achieves significant wake enhancement and improves the recognition of detail wake features. Full article

Photonic integrated interferometric imaging systems (PIISs) provide a compact solution for high-resolution Earth observation missions with stringent size, weight, and power (SWaP) constraints. As an indirect imaging method, a PIIS exhibits fundamentally different noise response characteristics compared to conventional remote sensing systems, and its imaging performance under practical operational scenarios has not been thoroughly investigated. The primary objective of this paper is to evaluate the operational capabilities of PIISs under remote sensing conditions. We (1) establish a signal-to-noise-ratio model for PIISs with balanced four-quadrature detection, (2) analyze the impacts of intensity noise and turbulent phase noise based on radiative transfer and turbulence models, and (3) simulate imaging performance with WorldView-3-like parameters. The results of the visibility signal-to-noise ratio (SNR) analysis demonstrate that the system’s minimum detectable fringe visibility is inversely proportional to the reciprocal of the sub-aperture intensity signal-to-noise ratio. When the integration time reaches 100 ms, the minimum detectable fringe visibility ranges between ${10}^{-2}$ and ${10}^{-3}$ (at 10 dB system efficiency). Imaging simulations demonstrate that recognizable image reconstruction requires integration times exceeding 10 ms for 10 cm baselines, achieving approximately 25 dB PSNR and 0.8 SSIM at 100 ms integration duration. These results may provide references for potential applications of photonic integrated interferometric imaging systems in remote sensing. Full article