The radar surface echo can be separated into coherent and incoherent components by statistical approaches, and the coherent component can be described by a backscattering model related to the RMS height. According to backscattering models for fractal surfaces, the coherent power in decibels decreases with RMS height on a scale independent of the wavelength at a rate depending on the Hurst exponent and the roughness scale. We extract the coherent power in four research areas by fitting the amplitude distribution of the Martian surface echoes recorded by the SHARAD radar, and compare the coherent power with the RMS height derived from pulse width of the MOLA laser altimeter. Scatter plots of squared MOLA-derived RMS height-coherent power are drawn to estimate the rates of coherent power fall-off by linear fitting, and the fitting power fall-off rates are compared to the Hurst exponents derived from digital terrain models in those areas. The fitting rates decrease with the Hurst exponent, similar to the theoretical rates. However, the fitting rates decrease with the Hurst exponent more sharply than the theoretical prediction. We explain the mismatch with a linear assumption between different roughness parameters, which helps to estimate the Hurst exponent, and a significant discrepancy between the wavelength and the roughness scale might influence the estimation results due to the scaling dependence of the Hurst exponent. This paper offers an opportunity to learn about the Hurst exponent at a tens-of-meter scale.

Objective Methane (CH4) is a hazardous, flammable, and explosive gas with significant greenhouse potential. It readily ignites in air upon exposure to open flames, underscoring the critical importance of monitoring leaks to ensure public safety and support climate governance. CH4 possesses a global warming potential (GWP) 27.9 times that of carbon dioxide over a 100-year period, designating it as a critical target for climate change mitigation. Effective monitoring of CH4 emissions is therefore essential for risk reduction in industrial settings and addressing environmental challenges. Conventional passive optical imaging techniques, such as optical gas imaging cameras, are constrained by environmental variables including background radiation and meteorological conditions, limiting their capability for quantitative measurement. Although active detection methods offer improved accuracy, they often lack robustness over long distances or on low-reflectivity targets. This paper introduces a novel active CH4 imaging sensor system that combines wavelength modulation spectroscopy with first harmonic normalized second harmonic detection (WMS-2f/1f) method and synchronized mechanical scanning, overcoming limitations inherent in both active and passive CH4 detection approaches. Methods The system employs a distributed feedback (DFB) laser operating at 1653.74 nm, corresponding to a strong CH4 absorption line located at 6046.94 cm(-1), as documented in the HITRAN database. This wavelength selection minimizes spectral interference from water vapor and carbon dioxide, ensuring high specificity in CH4 detection. The system incorporates a laser rangefinder and a pan-tilt unit capable of two-dimensional mechanical scanning across 360 degrees horizontally and 120 degrees vertically. Multi-sensor data fusion is utilized to integrate angular position, distance, and CH4 concentration inversion, enabling reconstruction of detailed two-dimensional CH4 distribution images. Key signal processing techniques include WMS-2f/1f normalization for enhanced accuracy and a Savitzky-Golay filter to improve signal-to-noise ratio (SNR). The optical assembly within the scanning head comprises a DFB laser, fiber collimator, Fresnel lens, and an InGaAs photodetector. Experimental validation includes calibration within a gas cell at eight concentration levels from 1000 & times;10(-6)& centerdot;m to 15000 & times;10(-6)& centerdot;m. CH4 plume imaging is further evaluated using Lambertian targets with reflectivity between 10% and 90%, demonstrating accurate CH4 mapping at distances of 10 m and 30 m under varied conditions. Results and Discussions Calibration tests using a CH4 gas cell demonstrate a strong linear response between the 2f/1f signal amplitude and CH4 concentration (R-2=0.9976), confirming the system's measurement reliability. Imaging performance is evaluated at 10 m and 30 m range using Lambertian targets with reflectivities of 10%, 50%, and 90%. At 10 m range, the system accurately reconstructs spatial concentration distributions of CH4 gas bags (20%?100% volume fractions) while preserving structural details across all reflectivity levels. At 30 m range, spatial detail is reduced, but the system still clearly identifies methane gas contours against high-reflectivity backgrounds (50%?90%). Even under low-reflectivity (10%) conditions, the developed prototype still enables decent qualitative methane imaging. Quantitative analysis further supports these findings: at 10 m range, R-2 values between measured and actual concentrations are 0.95, 0.97, and 0.99 for 10%, 50%, and 90% reflectivity, respectively. At 30 m range, the corresponding R-2 values are 0.82, 0.93, and 0.98, demonstrating reliable linear fitting (R-2 >= 0.83) even under challenging conditions. Absolute quantification tests at 10 m show average relative errors of 3.17%, 5.50%, and 11.89% for 90%, 50%, and 10% reflectivity, respectively. The system's quantification accuracy remains within 15% across all scenarios, affirming its robustness and suitability for static CH4 measurements. Conclusions This study presents an active CH4 imaging sensing system that synergistically combines WMS-2f/1f with synchronized mechanical scanning. The system achieves a linear fit coefficient of R-2 no less than 0.83 under demanding conditions (30 m range, 10% reflectivity) and keeps quantification accuracy within 15% even at low Lambertian reflectivity. Based on a DFB laser and a single-point detector, the instrument offers a favorable balance between performance and cost, showing strong potential for industrial applications. Its portable design supports mobile deployment and real-time monitoring, addressing vital needs in CH4 leak detection and climate mitigation strategies. Future work will prioritize dynamic plume imaging and absolute concentration quantification to further advance industrial applicability.

The coded aperture hyperspectral imaging systems typically describe the imaging process using a decoupled "ideal coding model plus error" approach. However, in the long-wave infrared band, non-ideal coding of the mask component and stray light from unintended grating orders are deeply coupled with the encoding-dispersion process, rendering traditional models ineffective. This paper proposes a coupled corrected imaging model that accounts for both interferences and further considers their mutual coupling. A corresponding reconstruction strategy is then developed, which, combined with conventional estimation algorithms, enables full-scene data recovery. A laboratory gas detection experiment was conducted to compare the reconstruction performance of the traditional model, the partially corrected model, and the fully corrected model. Results demonstrate that, compared to traditional models, the proposed model effectively eliminates structured errors caused by these interferences: spatial striping artifacts are removed, the characteristic absorption peaks of ammonia are correctly reconstructed, and no fake peaks are introduced in the weak absorption bands, validating the effectiveness of the proposed model.

Context. Optical measurement is a powerful tool for retrieving the regolith physical properties of the lunar surface. Aims. It has been a long-standing question in planetary remote sensing whether laboratory measurements are consistent with remote sensing measurements. The sample return mission of Chang’e-5 (CE5) has provided an opportunity to answer this question. Methods. For this work we performed photometric, linear and circular polarimetric, and reflectance spectroscopic measurements of the Chang’e-5 surface scooped regolith (soil) sample CE5C0600. Results. Our results show that the CE5 regolith exhibits both a strong opposition effect and a pronounced forward-scattering lobe, and a moderate contrast between its minimum and maximum reflectance values compared to the in situ measurements of Chang’e-3 and −4. A slight monotonic phase reddening trend is observed with increasing phase angle, while no clear colorimetric opposition effect was found at small phase angles The regolith shows maximum linear polarization at large phase angles, ∼16 at 633 and ∼21% at 532 nm, slightly higher than the values reported in ground-based observations and laboratory measurements on the Apollo and Luna samples. The circular polarization ratio increases as the phase angle decreases, consistent with previous observations of the Apollo samples. Compared with orbital, in situ,and ground-based observations of the CE5 landing site, the laboratory-measured regolith exhibits higher reflectance but a very similar spectral slope, suggesting a higher degree of compaction in the Earth environment. Conclusions. Studies of lunar samples with varying porosities and space weathering degrees are needed to better understand their behavior under in situ condition, enabling their use as a reliable ground truth for current and future Lunar missions.

High-resolution global catalogs of lunar impact craters are fundamental to understanding surface evolution, impact flux, and planetary chronology. This study presents the LUC-GRAS200 catalog, a new global data set containing approximately 10.7 million craters with diameters ranging from 0.2 to 2,050 km. The catalog integrates multi-source imagery and topographic data with deep learning-based detection, followed by systematic morphometric extraction and auxiliary secondary crater likelihood assessment. All results are interpreted within a quantified framework of detection completeness and systematic uncertainties. Observable spatial and scale-dependent variations in crater density, saturation equilibrium, and morphometric parameters (depth-to-diameter ratios, slopes, and rim height-to-diameter ratios) are documented. These patterns include hemispheric asymmetry (more stable at diameters >= 5 km), mare-highland contrasts that decrease toward smaller diameters, and latitudinal gradients most evident at sub-kilometer scales. Saturation coverage (R > 0.3) increases with crater diameter and shows regional differences, with higher values tending to occur in polar and highland regions. Morphometric parameters exhibit systematic variations across geological settings, with higher mean values generally observed in highland terrains compared to mare regions. The catalog extends systematic crater characterization to sub-kilometer diameters while explicitly documenting residual uncertainties, particularly for small-diameter craters and high-latitude regions influenced by illumination conditions, DEM-resolution transitions, and secondary crater contributions. These observational constraints provide a framework for crater chronology, impact flux studies, surface evolution analyses, and future lunar mission planning.

To address the demand for wide-swath, high-resolution short-wave infrared (SWIR) imaging on resource-constrained spaceborne platforms, this study presents the design and on-orbit validation of a compact dual-channel push-broom (line-scanning) imaging system. The system adopts a transmissive optical architecture and a centralized, compact electronic control unit (ECU) configuration. By interleaving and mosaicking sixteen InGaAs linear array detectors, the system achieves an imaging swath of approximately 187 km and a nominal ground sampling distance of about 24 m, while maintaining a total instrument mass of 10.62 kg and a power consumption of approximately 12 W, thereby demonstrating a high level of integration and efficient resource utilization. To address focal plane consistency issues arising from multi-detector mosaicking, a closed-loop leveling method was developed using the modulation transfer function (MTF) as the primary performance metric. Through defocus estimation and quantitative correction of protrusions on a SiC substrate, convergence toward a unified confocal focal plane among multiple detectors was achieved. On-orbit image quality assessment indicates that the full width at half maximum (FWHM) of the line spread function (LSF) for both channels is approximately 1.38 pixels, with favorable signal-to-noise ratio (SNR) performance. These results validate the effectiveness of the proposed focal plane leveling strategy as well as the opto-mechanical-thermal design of the system. The proposed approach provides a practical pathway for the engineering implementation and consistency control of multi-detector mosaicked SWIR payloads under stringent resource constraints.

Infrared imaging plays a fundamental role in commercial aerospace applications, providing reliable sensing under challenging conditions such as nighttime or cloudy weather. The spatial resolution of infrared images, however, remains constrained by payload size, power consumption, and detector performance. In this study, we developed and realized a high-resolution mid-wave infrared imaging system based on a reflective microscan mechanism with a fast-steering mirror for precise sub-pixel displacements, integrated with a multi-frame super-resolution reconstruction method. An explicit degradation and downsampling model incorporating sub-pixel shifts is formulated and solved via a joint total variation (TV)–alternating gradient (AG) regularization strategy, where TV suppresses high-frequency noise and AG enhances directional weak edges characteristic of infrared targets. By integrating these strategies, the reconstruction simultaneously reduces noise, preserves weak directional edges, and mitigates the impact of sub-pixel motion errors. Experimental results demonstrate that the proposed approach enhances spatial resolution and edge fidelity, highlighting its practical value for compact commercial aerospace infrared payloads.

Long-wave infrared imaging spectrometers are capable of spectrally resolving and spatially imaging the infrared radiation from detected targets. However, achieving high sensitivity poses a significant challenge. This is due to the strong infrared background radiation generated by instruments themselves at ambient temperatures, coupled with the spectral subdivision of the target signal. To address this, we propose an approach that enhances detection sensitivity by increasing signal throughput and incorporating ambient-temperature background suppression. The proposed method replaces the traditional single slit with an aperture-encoding slit array. This increases the incidence flux of target radiation and spatially encodes it. The encoded information, after dispersion and background suppression, is acquired and subsequently decoded via a reconstruction algorithm, enabling snapshot spectral imaging. The prototype covers a spectral range of 7.6-11.35 µm, with a spectral resolution better than 50 nm and a temporal resolution of 10 Hz. This paper details the opto-mechanical design, alignment and testing, and system evaluation. Experimental results demonstrate that the approach achieves fine spectral images of detected targets under ambient opto-mechanical conditions, enabling the detection and identification of dynamic targets. Unlike conventional cooling solutions, the approach avoids the additional weight, volume, and power consumption associated with opto-mechanical cooling. This allows the system to adapt to more lightweight platforms, showing great potential for future applications on unmanned aerial vehicles, as well as airborne and spaceborne platforms.

Hazardous gas leaks detection and quantitative analysis are crucial for industrial safety and environmental monitoring. Existing infrared gas imaging systems face challenges in combining wide-field detection with high-resolution identification, and are unable to simultaneously capture spatial and spectral information, which limits recognition accuracy and reliability. For this, a variable-focus multispectral camera (VFMC) based on spatial amplitude-splitting and continuous zoom is proposed in this paper. Operating in the 7-14µm wavelength range, the system provides continuous zoom from 22.5 mm to 75 mm, with its snapshot six-channel spectral imaging capability and an F/1 large-aperture design, the camera delivers high sensitivity, high spatial resolution, and simultaneous multispectral acquisition, significantly improving detection performance and identification reliability. This advancement holds considerable importance for rapidly detecting and analyzing gas leaks in complex environments.

Wide field-of-view (FoV) LiDAR sensors provide dense geometry across large environments, but existing LiDAR-inertial-visual odometry (LIVO) systems generally rely on a single camera, limiting their ability to fully exploit LiDAR-derived depth for photometric alignment and scene colorization. We present Omni-LIVO, a tightly coupled multi-camera LIVO system that leverages multi-view observations to comprehensively utilize LiDAR geometric information across extended spatial regions. Omni-LIVO introduces a Cross-View direct alignment strategy that maintains photometric consistency across non-overlapping views, and extends the Error-State Iterated Kalman Filter (ESIKF) with multi-view updates and adaptive covariance. The system is evaluated on public benchmarks and our custom dataset, showing improved accuracy and robustness over state-of-the-art LIVO, LIO, and visual-inertial SLAM baselines.

The spectral selectivity of underwater multiwavelength single-photon LiDAR offers a promising pathway to discriminate target materials beyond conventional geometric imaging. However, the complex interactions among wavelength-dependent water attenuation, target reflectance, and scattering-induced waveform distortion remain poorly quantified. This study establishes a comprehensive theoretical and experimental framework linking these factors, validated through controlled experiments across two water turbidity levels (attenuation coefficients of 0.1 m−1 and 2.0 m−1), six wavelengths (490–570 nm), and diverse target types. We demonstrate that target ranging bias exhibits a wavelength-dependent linear trend (8.3 ps/nm) in turbid waters. This phenomenon is fundamentally attributable to forward-scattering-induced centroid shifts rather than true spatial displacements, a mechanism we quantify through comparative peak-detection and Gaussian fitting analyses. Contrary to intuitive expectations, we reveal that spectral discrimination efficacy decouples from received photon counts. Principal component analysis confirms that a multidimensional spectral feature space enables accurate target clustering independent of absolute intensity, with specific bands (e.g., 510 nm and 550 nm) exhibiting heightened sensitivity to material signatures. These findings establish that underwater target recognition is primarily influenced by the spectral contrast between target reflectance and water transmission windows, rather than solely depending on received photon counts, providing a robust physical basis for next-generation underwater LiDAR optimization.

In thermal infrared hyperspectral remote sensing, accurate retrieval of land surface temperature (LST) and land surface emissivity (LSE) is fundamental to quantitative applications. Most existing temperature and emissivity separation (TES) algorithms primarily focus on noise suppression, adaptation to specific surface types, or improvements in computational efficiency, while relatively limited attention has been paid to retrieval disturbances caused by ozone emission. To address this issue, this study proposes the OWTES algorithm, whose core concept is to enhance the weighting of ozone-sensitive spectral bands within the cost function. By strengthening the error constraints in this spectral region during the inversion process, OWTES effectively mitigates the adverse impact of noise on the retrieval procedure. Experimental results demonstrate that OWTES achieves higher retrieval accuracy for both LST and LSE, with particularly significant advantages under low-temperature and high-noise conditions. Compared with several representative TES algorithms, OWTES improves LST retrieval accuracy by an average of approximately 0.75 K and enhances LSE retrieval accuracy by about 58%. In addition, the algorithm maintains the lowest error level when validated using measured emissivity data, demonstrating high stability and reliability. These results indicate that OWTES can effectively preserve surface spectral characteristics and improve TES retrieval accuracy under complex observation conditions. Overall, the proposed OWTES method provides a more stable and reliable solution for temperature and emissivity separation in thermal infrared hyperspectral remote sensing.

The Tianwen-2 probe carries an asteroid core-scanning radar (ACSR) to study the internal structures of near-Earth asteroid 2016 HO _3 and main-belt comet 311P. Radar signals are often contaminated by surface clutter, which can overlap with weaker subsurface echoes due to propagation attenuation. This paper proposes a surface-clutter separation method based on cross-correlation and moment-matching algorithms. It realizes effective separation by performing joint calibration of the position and amplitude of surface clutter. The simulation results demonstrate that this method can effectively separate surface clutter across various detection scenarios. Ground-test data further validate the method’s capability to separate dominant surface clutter in in situ detections. These results indicate that the approach is effective for investigating the internal structures of asteroids and comets in the Tianwen-2 mission.

In response to the increasing demand for marine resource development, environmental monitoring, and maritime security, traditional underwater detection technologies are encountering significant challenges. Particularly in dynamic marine environments, the precise retrieval of chlorophyll-a concentration under disturbed conditions has emerged as a critical bottleneck in underwater optical remote sensing. This study introduces and validates a multi-wavelength underwater laser radar (LiDAR) system and method utilizing single-photon detection. It systematically examines the mechanisms by which wavelength selection, water turbidity, and target characteristics influence detection performance. Through the design of experiments involving seven typical water conditions (clean water, and combinations of two chlorophyll-a concentration and three levels of disturbance) and six wavelengths (490-570 nm), we conducted a comprehensive analysis of the variation characteristics of the raw LiDAR signal, range-corrected signal, filtered signal, and chlorophyll-a retrieval results. The findings indicate that an increase in chlorophyll-a concentration elevates the signal attenuation rate by 15-30 %, while turbulent disturbances introduce 10-25 % signal fluctuations. Filtering processing enhances the signal-to-noise ratio by 30-50 %, reducing the relative signal deviation errors to less than 5 %. Multi-wavelength joint retrieval significantly improves the vertical profile resolution of chlorophyll-a concentration, with layered structures particularly distinct within the 8-12-meter range. This study demonstrates that the multi-wavelength singlephoton LiDAR system, through the optimization of wavelength selection and processing algorithms, can effectively mitigate the impact of disturbances and achieve high-precision retrieval of bio-optical parameters in dynamic waters, offering a novel technical solution for marine environmental monitoring and underwater target identification.

Introduction: China's Tianwen-2 mission is designed to achieve orbital exploration and sample return from the near-Earth asteroid (2016 HO3), as well as a flyby exploration of the main-belt comet (311P), in a single launch [1]. Equipped with an Asteroid Thermal Emission Spectrometer (ATES), the mission aims to determine the surface mineral composition and thermophysical properties of both targets, thereby shedding light on their formation and evolutionary mechanisms [2]. However, on airless bodies like asteroids [3], the lack of interstitial gas limits heat transfer within the shallow subsurface to inefficient inter-particle radiation and contact conduction. This creates a steep thermal gradient within the top few hundred micrometers, which significantly alters thermal emission spectral features (e.g., shifting the Christiansen Feature (CF) to higher wavenumbers and increasing spectral contrast) [4-9]. Consequently, remote sensing thermal emission spectra cannot be directly interpreted using standard spectral libraries acquired under terrestrial conditions. To accurately interpret thermal infrared remote sensing data from airless bodies, laboratory thermal emission spectroscopy systems that simulate the environments of airless bodies are strictly required. Several such systems have been established internationally to simulate airless surface environments, including Brown University's ALEC [10], Oxford University's SLEC [11] and PASCALE [12], and Stony Brook University's PARSEC [13]. However, there is currently no comparable facility in China. To address this gap, this abstract introduces a newly, independently developed thermal emission spectroscopy measurement system (ChaSALE) designed for airless bodies such as the Moon and asteroids.Design and Implementation of the ChaSALE: The ChaSALE primarily consists of a vacuum vessel, a 60K cryogenic helium circulation system, a sample cup assembly, a cryogenic off-axis parabolic mirror, a solar simulator and a control unit (Figure 1). The vacuum vessel provides the necessary vacuum environment for sample testing and includes a chamber, a pumping system and vacuum gauges. The system is capable of achieving a high vacuum of 8×10-9 bar inside the chamber. The 60K cryogenic helium circulation system cools the chamber to provide a cold background environment of < 100K, consisting of a thermal shroud, a cryocooler and associated piping. The sample cup assembly is used to hold and heat the test samples. From top to bottom, it comprises the sample receptacle, a heating module, a thermal insulation block, a support rod and a base. The heating module controls the sample temperature to simulate the varying thermal conditions on a planetary surface. The sample cup is designed with dimensions of Φ44 mm×5 mm. The cryogenic off-axis parabolic mirror collimates the divergent emission signals from the blackbody and the sample, directing the parallel beam into the spectrometer. A gold-coated aluminum mirror is utilized. To prevent the mirror's own thermal emission from contaminating the measurements, it is housed within a cold shield (Figure 1), which cools the mirror to approximately 150K during testing. The solar simulator is designed to replicate solar irradiation on the target body. The chamber is coupled to a Bruker Vertex 80V vacuum Fourier Transform Infrared (FTIR) spectrometer, which is equipped with a CsI beamsplitter and a liquid nitrogen-cooled Mercury Cadmium Telluride (MCT) detector. The operational capabilities and technical specifications of this system, alongside a comparison with similar international facilities, are summarized in Table 1.Figure 1: Schematic diagram of the thermal emission spectrum measurement system and its optical path.Table 1: Configurations and specifications of thermal emission measurement systems for the airless celestial bodies.Samples Test: To validate the capability of our newly developed system to reproduce thermal emission spectra, we selected a particulate mixture of olivine and calcite (70 wt.% olivine and 30 wt.% calcite) with well-characterized spectral features as a test sample. We measured and derived the sample's emissivity under cryogenic vacuum conditions, and the results are presented in Figure 2. By comparing our data with standard mineral spectra for olivine and calcite, key diagnostic features can be clearly identified. For olivine, the CF at ~1100 cm-1, the Transparency Feature (TF) at ~790 cm-1, and the Reststrahlen Bands (RB) located between them are distinctly resolved. Similarly, for calcite, the prominent spectral features at ~875 cm-1 and ~710 cm-1, alongside the broad absorption feature between 1400 cm-1 and 1200 cm-1, are readily apparent. These findings successfully demonstrate the system's reliability in accurately reproducing the thermal emission spectra of geological samples under simulated cryogenic vacuum environments.Figure 2: Validation results of the system’s ability to replicate sample thermal emission spectra.References: [1] Zhang et al. 2021, Nature Astronomy, 5(8): 730-731. [2] Li et al. 2024, Journal of Deep Space Exploration, 11(3): 304-310. [3] Wang et al., 2019, Spacecraft Environment Engineering, 36(6): 533-541. [4] Logan et al. 1970, Journal of Geophysical Research, 75(32): 6539-6548. [5] Logan et al., 1973, Journal of Geophysical Research, 78(23): 4983-5003. [6] Henderson et al., 1994, Journal of Geophysical Research: Planets, 99(E9): 19063-19073. [7] Bishop and Moersch, 2020, Cambridge: Cambridge University Press. [8] Donaldson et al., 2017, Icarus, 283: 326-342. [9] Shirley and Glotch, 2019, Journal of Geophysical Research: Planets, 124(4): 970-988. [10] Bramble et al., 2019, Review of Scientific Instruments, 90(9): 093101. [11] Thomas et al., 2012, Review of Scientific Instruments, 83(12): 124502. [12] Donaldson et al., 2021, Journal of Geophysical Research (Planets), 126(2): e06624. [13] Shirley and Glotch, https:∥ui.adsabs.harvard.edu/abs/ 2015LPI....46.2025S/.

There is an increasing demand for grating spectrometers, which are widely used in scientific research, industrial applications, and environmental monitoring due to their high resolution, wide spectral range, and high efficiency, at el. We propose a cryogenic, wide-band imaging spectrometer that achieves full spectral coverage by automatically switching among three gratings with varying groove densities. The three sub-channels utilize a shared optical path architecture, resulting in a compact opto-mechanical design. Combined with system-level cooling to suppress background noise, the temperature of the optical system and the detector are cooled to below 70 K and 4 K, respectively. The system achieves a spectral resolution of 86 nm, 164 nm, and 281 nm in the 6-11.5 & micro;m, 11.5-22 & micro;m, and 22-40 & micro;m bands, respectively. Optical simulation results shows a full-band Modulation Transfer Function (MTF) exceeding 0.45 is achieved. Tests conducted on human thermal radiation and representative gases (SF6 and CH4) demonstrate the feasibility of this cryogenic wide-band imaging spectrometer for the broad-spectrum analysis of intrinsic material properties. This technology holds significant potential value for the development and application of future high-sensitivity, broadband infrared detection instrumentation.

This study proposes a mid-infrared (MIR) spectral sensing scheme based on a metasurface filter array integrated with a physics-data dual-driven algorithm. Two types of metasurface structures, namely the silicon-based gold micro-hole array (Si-Au-MHA) and the silicon-based gold micro-pillar array (Si-Au-MPA), were designed through simulation to determine their structural parameters for fabrication, aiming to achieve spectral control across the 3-12 μm band. Samples were fabricated, and the transmission spectra were measured and validated. Furthermore, a physics-data dual-driven spectral reconstruction method combining regularized physical constraint with a neural network was introduced, demonstrating superior performance in both amplitude and spectral profile compared to purely physics-based or data-driven approaches. This work provides a viable solution for portable MIR spectral sensing applications.

Shortwave infrared (SWIR) imagery plays an important role in land–water boundary delineation, coastal monitoring, and complex aquatic environment observation. However, the spatial resolution of SWIR bands is usually lower than that of visible bands, which limits their capability to represent fine-scale targets and boundary structures. To address this problem, this study proposes MLE-ResUNet, a SWIR image super-resolution method that integrates along-track oversampling with visible-light-guided deep learning. The proposed method first exploits dual-view SWIR observations with sub-pixel displacement generated by increasing the sampling line rate in the push-broom imaging process. A maximum likelihood estimation (MLE)-based physical prior module is then introduced to transform multi-view degraded observations into a physically consistent latent high-resolution prior. Finally, high-resolution visible images are used to provide edge, texture, and structural guidance, and a ResUNet-based network is employed for multi-source feature fusion and residual reconstruction. Based on multi-region measured data acquired by the LHRSI (Lightweight High-Resolution Spectral Imager) payload onboard the BlueCarbon-1A satellite, a SWIR super-resolution dataset covering typical urban, farmland, and coastal scenarios was constructed. Comparative experiments were conducted against PCA, BDSD, PanNet, GPPNN, and two additional lightweight-guided deep learning baselines, namely LGPConv and a CANConv-style visible-guided baseline. The results show that MLE-ResUNet achieves the best performance across different scenarios and consistently outperforms the comparison methods in terms of SSIM, SAM, ERGAS, and Q-index. The proposed method effectively enhances spatial detail recovery while maintaining favorable spectral consistency. Ablation experiments further demonstrate that both along-track oversampling information and the MLE-based physical prior contribute to improved reconstruction quality and more stable training convergence. These findings indicate that the proposed method can enhance fine-scale SWIR observation capability without substantially increasing hardware complexity, providing an effective technical solution for shoreline identification, land–water boundary extraction, and complex surface target monitoring.

Underwater laser signal attenuation challenges conventional detection, while single-photon LiDAR (SPL) with high sensitivity shows promise. Existing underwater SPL studies primarily focus on isolated parameters, while the coupled effects of environmental and system parameters remain insufficiently investigated. In this work, a 532 nm underwater SPL system was developed to systematically explore multi-parameter coupling mechanisms in laboratory water tanks, including air and three turbidity levels, three detection distances, four laser energy levels, three integration times, and seven targets. This provides quantitative guidance for optimizing SPL systems in complex underwater environments. The results show that the SPL system maintained sub-nanosecond ranging precision, with the standard deviation (SD) of the ranging measurement at 50 cm being 0.0117 ns under low turbidity (0.11 m−1) with 50% laser energy, while under high turbidity (4.2 m−1) conditions, it increased to 0.0338 ns. At 100 cm, the SD was 0.0187 ns in low turbidity and rose to 0.0877 ns in high turbidity. Furthermore, the inversion error of the highly reflectivity minerals was kept within 3%, and the inversion value of reflectivity decreased exponentially with the increase of turbidity. Moreover, there is an important discovery for the phenomenon of the forward shift of photon flight time detected for highly reflectivity targets. Longer integration times effectively enhanced the signal-to-noise ratio (SNR) under severe attenuation, whereas excessive laser energy risked detector saturation. These findings provide a systematic characterization of how multifactor coupling governs SPL signal dynamics. The results validate the feasibility of SPL for complex underwater detection and offer theoretical insights and technical guidance for future marine applications in resource exploration, environmental monitoring, and national security.

Recent advances in infrared gas leak detection have substantially improved learning-based detection and quantification across different imaging instruments. However, achieving gas detection, classification, and quantitative analysis within a unified system remains challenging because of limited real-time capability, signal instability, and information loss caused by interchannel inconsistency during normalization. To address these issues, this article presents a framework with information-preserving preprocessing (IPP) in our uncooled snapshot multispectral infrared imaging system. A radiometric signal model is established to characterize information degradation in the raw-to-digital conversion process, and the relative background radiance contrast (RBRC) metric is introduced to preserve absorption-related spectral variations across channels after normalization. Methane and ammonia are used as representative gases to validate the quantitative performance in controlled gas cell experiments under different background temperatures. With $\Delta T$ ranging from 10 to 25 K, the proposed method achieves average relative errors of 11% for methane and 7.8% for ammonia at 3000 ppm $\cdot $ m, while the error increases under low-concentration conditions with weak absorption. Outdoor leakage experiments further show that the proposed preprocessing improves interchannel consistency and enhances gas detection performance across multiple mainstream object detectors. In addition, the detector-guided postprocessing enables quantitative plume segmentation and contrast-enhanced visualization for gas analysis.