Event cameras are a novel type of visual sensor inspired by the biological retina， capable of asynchronously capturing pixel brightness changes with microsecond-level temporal resolution. Unlike traditional cameras that capture frames at fixed intervals， event cameras only trigger an event when pixel brightness exceeds a preset threshold. This unique mechanism endows event cameras with an ultra-wide dynamic range of up to 140 decibels and exceptional temporal resolution， granting them significant advantages in high-speed， high-dynamic-range scenarios such as object tracking， motion detection， and Simultaneous Localization and Mapping （SLAM）. These capabilities enable event cameras to capture rapid movements and subtle changes in dynamic scenes that conventional cameras might miss. However， event cameras have a significant limitation： they can not directly capture grayscale images in static scenes. This is because when a scene is stationary and light intensity remains constant， the camera detects no change in light intensity， failing to meet the conditions for event triggering. These characteristics restrict their application in scenarios requiring complete brightness information， such as static object or scene recognition and measurement in traditional image processing tasks. Consequently， despite their ultra-high dynamic range， temporal resolution， and exceptional performance in dynamic environments， event cameras still face challenges in applications demanding detailed， continuous brightness data acquisition under static conditions.

To address the challenge of capturing static scenes with event cameras， this paper introduces a novel approach using mechanical shutter mapping for imaging. The core innovation lies in modulating brightness variations in static scenes through the rotation of a mechanical shutter， triggering events even in the absence of light intensity changes. By adjusting the shutter's rotation speed at varying rates， discrete events are generated， which are then reconstructed into High Dynamic Range （HDR） grayscale images. This technique overcomes a significant limitation of traditional event cameras， which struggle to capture static scenes due to the lack of natural light variations. A key aspect of this method is the calibration process， which ensures that the generated event data is accurately aligned with the actual light intensity of the scene， enabling precise and accurate grayscale image reconstruction. In this setup， the mechanical shutter acts as an active driving mechanism， inducing event generation by modulating the scene's brightness. This allows the event camera to capture dynamic information in static scenes， where traditional event cameras would otherwise fail to register changes. As a result， this method significantly enhances the imaging capabilities of event cameras， broadening their potential applications in static environments with minimal or no natural light variations.

Experimental results show that the reconstructed HDR images achieve a dynamic range of up to 112 dB. This range allows the event camera to capture fine details in both dark and bright areas of the scene， overcoming the limitations of conventional cameras with fixed dynamic ranges. The calibration process further improves the accuracy of grayscale image reconstruction. Our experimental results demonstrate that shutter-based techniques successfully reconstruct grayscale images of static scenes under extreme lighting conditions. Compared to prior methods， this approach significantly improves image quality， reduces grayscale distortion， and preserves details often lost in conventional event reconstruction techniques. By generating events through controlled brightness variations， this method enhances the imaging capabilities of event cameras in static environments. Furthermore， the mechanical shutter mechanism facilitates portability， enabling adaptation to multiple event camera models and enhancing the system's versatility and practical applicability. Beyond expanding event cameras' capabilities in static scenes， this approach also provides a solution for event cameras operating under complex lighting conditions. Our shutter mapping technology offers a controlled event triggering mechanism， enabling event cameras to function in scenarios where traditional methods fail. This opensnew possibilities for event cameras in fields requiring high-quality grayscale images， such as industrial inspection.

This paper proposes and validates a shutter-mapped event camera method for grayscale imaging in high-dynamic-range static scenes. The core innovation of this approach lies in introducing a mechanical shutter as an active driving mechanism， which effectively overcomes the limitation that event cameras cannot generate event streams in static scenes due to the absence of brightness changes. By modulating the scene's brightness using controlled shutter rotations， the event camera can trigger events even in stationary conditions. Experimental results demonstrate that this method successfully reconstructs grayscale images of high-dynamic-range static scenes， achieving a dynamic range of up to 112 dB under extreme illumination conditions， all using a frameless event camera. Compared to existing methods， our approach significantly improves reconstruction quality， reduces grayscale distortion， and preserves fine details. Additionally， the proposed mechanical shutter triggering mechanism offers versatility and portability， providing a controllable active refresh mechanism that is compatible with various event camera models. In summary， the shutter mapping method extends the capabilities of event cameras in static scenes， enabling high-quality HDR grayscale image reconstruction. By inducing brightness variations through mechanical shutter actuation， event cameras can generate event streams and reconstruct HDR images， even in static scenes with extreme lighting conditions.

A Microwave Photonic Filter （MPF） is a device that filters microwave signals by first modulating them into the optical domain， then processing them using optoelectronic components. Compared to traditional electronic microwave filters， they exhibit advantages such as superior frequency tuning range， flexible spectrum reconfiguration， and inherent immunity to electromagnetic interference， etc. These benefits make MPFs highly promising for widespread applications in wireless communication， radar， and electronic warfare systems. With the advancement of integrated optoelectronic technologies， MPFs are progressively evolving from discrete fiber-optic devices towards integrated solutions. This transition aims to substantially reduce their size， weight， power consumption， and cost. In this review， firstly the system architectures and working principles of both incoherent and coherent integrated MPFs are presented. Subsequently， recent research advances in these two categories of MPFs are reviewed.

For incoherent integrated MPFs， multi-tap configurations are typically adopted， utilizing Finite Impulse Response （FIR） digital filter architectures rooted in discrete signal processing algorithms. Some key integrated optical components enabling dispersion-delayed sampling in multi-tap MPFs are given， such as integrated high-dispersion chips， multi-wavelength light sources， and spectral shaping chips. By adopting these functional chips into microwave photonic filter links， some MPFs with good frequency tuning capabilities and out-of-band RF suppression have been reported. But the limited number of taps and unattainable complex tap coefficients resulting in insufficient spectral reconstruction capability of the achieved incoherent MPFs. To date， only aforementioned integrated chips have been integrated into microwave photonic filter links， while other critical components still rely on discrete fiber-based devices. Incoherent MPFs with higher integration levels remain unreported in the literature.

For coherent integrated MPF， typically microwave signals are modulated onto a single-wavelength laser source， where various integrated optical filters are adopted to spectrally shape modulated optical signal， followed by down-conversion at a photodetector to convert optical domain filtering response into microwave domain. Various integrated optical components to construct coherent MPFs such as Micro-Ring Resonator （MRR）/Micro-Disk Resonator （MDR）， nonlinear As2S3 waveguide with Stimulated Brillouin Scattering （SBS）， photonic crystal cavity， microsphere， phase shifted waveguide Bragg grating， Surface Acoustic Wave （SAW） based on suspended waveguide have been reviewed. Based on these integrated optical components， various MPF link architectures to realized band-stop and band-pass MPFs have been introduced. Band-stop MPFs can be realized through optical-to-microwave mapping based on Optical Single Sideband （OSSB） modulation. Furthermore， by employing Radio Frequency （RF） cancellation techniques via Unbalanced Optical Double Sideband （UODSB） modulation， this approach can overcome the limitation imposed by optical filter’s extinction ratio on RF suppression performance and enables band-stop MPF with RF rejection ratio larger than 60 dB. On the other hand， Band-pass MPFs can be realized through either by optical carrier separation and re-entry techniques enabling direct one-to-one mapping of optical band-pass responses to the microwave domain， or phase-to-intensity conversion schemes that transform optical band-stop filtering into microwave band-pass responses. In addition， some technologies to enhance MPF's frequency resolution have been introduced， such as improving quality factors of MRR/MDR with mode manipulation， incorporating on-chip narrow-band SBS gain/loss spectra， adopting SiO₂ microsphere， etc. Up to date， frequency resolution down to about ten MHz have been demonstrated for band-pass and band-stop MPFs. Building on recent advances in integrated optical filters for MPF links， this work futher surveys highly integrated microwave photonic filter chips implemented on Thin-Film Lithium Niobate （TFLN）， Silicon-On-Insulator （SOI）， and indium phosphide （InP） platforms， providing a comparative analysis of their respective advantages and limitations.

Finally， quantitative comparative analysis of key performance metrics of the reported incoherent and coherent integrated MPFs have been given. Some key technical challenges in integrated MPFs， including the trade-offs between filter's bandwidth and frequency tuning range， insufficient noise figure/out-of-band RF rejection ratio/frequency stability， immature heterogeneous integration， and broadband photonic packaging solution with low crosstalk and high RF integrity. Moreover， an outlook on the future development trends of integrated MPF is presented.

Precise micro-displacement measurement technology plays a critical role in real-time defect monitoring during manufacturing processes， ensuring adherence to accuracy standards and significantly reducing scrap loss. Chromatic confocal displacement measurement systems operate based on the principles of optical dispersion and confocal technology. Through chromatic encoding， a wavelength-axial position mapping relationship is established， while confocal imaging decodes the reflected spectrum. This enables real-time displacement measurement with sub-micrometer accuracy within a millimeter range， simultaneously providing nanometer-level resolution and robust environmental adaptability. The measurement range and accuracy are constrained by the axial dispersion and aberrations of the dispersive objective. To expand the measurement range and enhance the accuracy of the chromatic confocal displacement sensing system， a secondary dispersion objective based on Gradient-index （GRIN） fiber was designed in this study. The Physics-Informed Neural Network （PINN） algorithm was leveraged in conjunction with ZEMAX software simulation to broaden the system's chromatic dispersion while achieving comprehensive compensation and correction of aberrations in both the secondary dispersion objective and the pre-dispersion GRIN fiber.

Firstly， based on the working principle of chromatic confocal displacement sensors， a GRIN fiber-based chromatic confocal system was proposed. A pre-dispersion unit employing GRIN fiber was established according to its refractive index distribution and the Cauchy dispersion model. The relationship between wavelength and axial dispersion was derived. The chromatic focal shift of the GRIN fiber at different pitch numbers was simulated and analyzed. It was determined that at a GRIN fiber pitch number of m=5， an axial pre-dispersion of 1.496 mm could be achieved， with a linearity R² of approximately 95%. Subsequently， based on Hamiltonian optics theory， the aberrations introduced by the GRIN fiber were derived. Based on the calculated equivalent object position of the GRIN fiber pre-dispersion unit and aberration theory， the GRIN fiber aberrations were analyzed. A secondary dispersion objective was then specifically designed. Its dispersion performance was analyzed and aberrations were optimized using ZEMAX. Finally， to improve system resolution and correct aberrations， an aberration correction method employing PINN combined with ZEMAX for closed-loop verification was proposed. A dataset correlating “lens parameters” with “Zernike aberrations” was established using ZEMAX. Combined with aberration data from the pre-dispersion GRIN fiber， PINN was utilized to predict feedback and perform iterative optimization. This facilitated comprehensive aberration correction and optimized axial dispersion linearity.

Within the operating wavelength range， the corrected spherical aberration values were significantly lower than pre-correction levels， with particularly pronounced correction in the short-wavelength region. Post-correction spherical aberration values for all wavelengths were markedly optimized， demonstrating effective spherical aberration correction. The aberration correction model demonstrated strong generalization capability， and the overall model training was effective， confirming successful aberration correction. The effectiveness of the aberration correction methodology using ZEMAX software combined with the PINN algorithm for closed-loop verification was thus validated. Following algorithmic optimization， a new optimized dispersive objective lens group was obtained. Results demonstrate that the maximum system aberration was reduced below 10 μm. Total axial dispersion reached 4.34 mm with a linearity R² of 99.84%. Theoretical resolution was approximately 25 nm. In the optimized system， the RMS spot radius at the focal point for each wavelength across the visible spectrum was smaller than the Airy disk， achieving diffraction-limited performance and meeting high-precision displacement measurement requirements. This study provides novel chromatic confocal system optimization， enhancing displacement measurement performance and advancing practical engineering implementation.

The primary objective of this study is to design and experimentally validate a low-loss edge coupler based on a bi-level taper structure on the thin-film lithium niobate platform， specifically targeting efficient coupling with standard single-mode fibers having a mode field diameter of 6 μm at the 1 310 nm wavelength， to address the critical challenge of high coupling losses between Thin-film lithium niobate waveguides and optical fibers that hinder practical applications in integrated photonic systems such as fiber optic gyroscopes， aiming for a solution compatible with mass production via deep ultraviolet lithography while maintaining low optical loss and high alignment tolerance.

To achieve this， the coupler design incorporates two sequentially fabricated inverted tapers—a fully etched lower taper and a partially etched upper taper—within a silicon dioxide cladding， and the structural parameters were rigorously optimized using three-dimensional finite-difference time-domain simulations to maximize the mode field overlap integral between the waveguide and fiber， where key geometric variables including the taper lengths L₁ and L₂ （both set equal to L for simplicity）， the lower taper tip width W₁， the upper taper tip width W₂， the lower taper output width W₃， and the straight waveguide width W₄ were systematically varied to assess their impact on coupling efficiency， with initial simulations determining an optimal taper length L of 300 μm to satisfy adiabatic conditions and avoid excessive transmission loss or fabrication-induced defects， followed by width optimizations revealing optimal values of W₁ at 0.2 μm， W₂ at 0.2 μm， W₃ at 3.5 μm， and W₄ at 1.2 μm for single-mode operation， while additional analysis of the silicon dioxide upper cladding thickness indicated that a minimum thickness of 3 μm is essential to confine the mode effectively and prevent vertical leakage， with negligible efficiency variation between 3 and 6 μm.

Fabrication involved electron beam lithography for rapid prototyping and validation， where X-cut Thin-film lithium niobate with a 300 nm thick lithium niobate layer on a 4.7 μm silicon dioxide substrate was patterned using two Electron beam lithography steps followed by inductively coupled plasma-reactive ion etching to define the upper and lower tapers sequentially， and a 6-micrometer silicon dioxide cladding was deposited via a combination of low-pressure chemical vapor deposition and plasma-enhanced chemical vapor deposition to ensure density and minimize hydrogen-related losses. Experimental characterization employed a 1 310 nm superluminescent diode source and single-mode fibers in a cut-back method setup to measure total insertion loss， yielding a coupling loss of approximately 2.3 dB per facet for the optimized design， with the straight waveguide propagation loss separately quantified as 0.47 dB per centimeter， and scanning electron microscopy imaging confirmed the fabricated structure but indicated an approximate 110-nanometer lateral misalignment between the upper and lower tapers， though subsequent Finite-difference time-domain simulations demonstrated that such misalignments up to ±300 nm introduce negligible additional loss below 0.03 dB， affirming high fabrication tolerance. Further experimental sweeps of parameters W₁ and L showed consistent trends with simulations， where coupling loss decreased with increasing L up to 300 μm and increased with W₁ above 0.2 μm， and comparative analysis with existing coupler designs highlighted that this bi-level taper structure achieves a favorable balance between performance and process complexity， requiring only two etching steps and avoiding reliance on costly ultra-high numerical aperture or lensed fibers， thus enabling practical， low-cost deployment in fiber gyroscope applications.

In conclusion， the proposed bi-level taper edge coupler successfully demonstrates low coupling loss， robust manufacturability with substantial alignment tolerances， and full compatibility with standard single-mode fibers and deep ultraviolet lithography mass production， thereby providing a viable pathway for scalable integration of Thin-film lithium niobate based photonic devices.

Mid-wave infrared interference spectral imagers possess unique advantages in gas detection and identification due to their wide characteristic spectral coverage， high-throughput detection capability， and multi-channel sampling. Particularly in daily inspection and early warning of chemical gases and rapid emergency response to leakage scenarios， they can provide early warnings of disasters at the initial stage of gas leakage， preventing the situation from escalating. After a gas leak occurs， without requiring personnel to enter the site， they can quickly identify the type of leaking gas and the distribution of its diffusion concentration， providing first-hand on-site data for the evaluation of emergency response plans. However， traditional point-scan and area-scan interference spectral imaging configurations face significant limitations in enhancing lightweight， compact design， and stability. It is of great significance to research and design interference spectral imaging instruments that meet the high demands for mobility， adaptability to complex environments， field of view coverage， and lightweight compactness in specific application scenarios. Additionally， as interference spectral imagers require high precision in detector pixel intensity detection， it is necessary to study the analysis and suppression methods of infrared stray radiation in complex scenarios.

This paper proposes a spectral imaging system based on static interference modulation using a stepped micro-mirror. The optical configuration of the system is shown in Figure 1. The scanning telescope imaging lens assembly achieves wide-field one-time convergence imaging onto the stepped micro-mirror for interference modulation， and the image is then relayed onto the detection focal plane through the relay imaging lens group. A cylindrical design is introduced to compensate for the high-order astigmatism introduced by the interference beam-splitting system. Achromatic broadband design and athermalization across a wide temperature range are achieved through hybrid refractive-diffractive and aspheric designs， resulting in a static Modulation Transfer Function （MTF） better than 0.7 at the cutoff frequency. To analyze infrared stray radiation， a stray radiation model for the interference spectral imaging system was constructed. The materials and surface radiation scattering characteristics of the optomechanical structure were defined， and ray tracing was performed. Based on the tracing results， a stray radiation suppression structure was designed， achieving infrared radiation suppression at the level of 10⁻⁵.

The telescope imaging lens group was optimized with an image-space telecentric design， while the relay imaging lens group adopted an object-space telecentric design， achieving a perfect match in a dual-high telecentric optical system. By employing hybrid refractive-diffractive and aspheric designs， the system demonstrated excellent performance in the mid-wave infrared band of 3 μm-5 μm across a temperature range of -40 ℃ to 60 ℃. The static MTF exceeded 0.7 at 17 lp/mm， distortion was controlled within 0.2%， and the RMS radius of the imaging spot was less than 5.9 μm， meeting all imaging quality requirements. A stray radiation simulation model for the interference spectral imaging optomechanical system， as illustrated in Figure 7， was constructed. Stray radiation tracing was performed for typical field light paths， and based on the analysis results， efficient suppression was achieved through blackbody extinction treatment and dedicated stray radiation suppression structures. This reduced the infrared stray radiation energy ratio from an initial level of 10⁻² to 10⁻⁵. Imaging detection experiments on long-distance target scenes using an engineering prototype demonstrated excellent image quality. The MTF test of the prototype of high-precision alignment principle shows that the actual MTF of the designed imaging system is better than 0.32 at the cut-off frequency.

The infrared spectral imaging system based on static interference modulation with a stepped micro-mirror successfully achieves high-quality remote sensing imaging， identification and analysis of gases. The adoption of achromatic methods using cylindrical lenses and hybrid refractive-diffractive lenses， together with the stray radiation suppression method proposed in this paper， has all yielded the expected effects in optimizing imaging quality， which is proven to be effective and can serve as a reference for research in the same field. In addition， the instrument's volume is reduced by a quarter and its weight by approximately 60%， which also provides a valuable contribution to the miniaturization process of such imaging systems.

All-time laser ranging to space debris is a critical direction in the development of future laser ranging systems. During Earth's shadow periods， however， debris objects receive no solar illumination and are invisible to optical cameras. In these conditions， telescope pointing corrections cannot rely on imaging and must instead depend on echo signal strength. Because debris moves rapidly and orbit prediction errors remain， even targets briefly captured within the field of view quickly drift out. This prevents stable tracking and reduces ranging success rates.

To address this challenge， this study introduces a novel approach by incorporating a fiber array into the laser ranging system. The array consists of a central fiber surrounded by six uniformly arranged multimode fibers. Each fiber is divided into two outputs： one reference fiber of equal length and one guiding fiber of varying lengths. The fourteen outputs are fused into a single fiber， which is then connected to a Superconducting Nanowire Single-Photon Detector （SNSPD）. By measuring the relative delays among echo signals， the incident fiber can be identified， enabling calculation of the target's offset direction in the field of view and guiding the telescope for tracking.

Experiments were conducted using the 1.2 m coaxial laser ranging system at Yunnan Observatory during May-June 2025. Cooperative targets with small orbit prediction errors were first selected as observation objects to verify the effectiveness of the fiber array method. After validation， the fiber array method was applied to space debris ranging experiments during Earth's shadow periods. The results demonstrate that the fiber array can effectively enhance the tracking capability of the ranging system for invisible targets. For cooperative targets equipped with retro-reflectors， the system efficiently extracted echo signals and accurately identified the incident fiber， thereby deriving the offset direction and achieving stable and reliable ranging. For non-cooperative debris， the current system shows certain limitations. As shown in Fig. 6（d）， debris with NORAD ID 28480 produced strong echoes that allowed identification of the incident fiber as F5. In contrast， debris with NORAD IDs 22220 and 21393， shown in Figs. 6（e）-（f）， yielded more dispersed echoes， making it difficult to accurately invert the incident fiber from time-delay information. This phenomenon mainly arises from temporal overlap of signals received by adjacent fibers. Specifically， debris generally exhibits a size effect， where differences in reflection depth across the surface broaden echo signals in the time domain. At the same time， the low surface reflectivity of most debris weakens the echoes and increases their susceptibility to background noise. Together， these factors cause temporal overlap among the multichannel data， which appears in the residual plots as clearly dispersed echo patterns and prevents reliable fiber identification based on inherent time delays.

To improve performance for non-cooperative targets， fiber parameters require targeted optimization. First， the delay difference between reference and guiding fibers should be increased so that the minimum channel separation exceeds three times the ranging precision， thereby reducing signal overlap. Second， the spatial arrangement of the array should be optimized to maximize the average channel delay difference， further suppressing inter-channel interference. Additionally， the current multimode fibers use a core diameter of 62.5 µm and cladding diameter of 125 µm， with the core occupying only 25% of the cross-sectional area. Under weak signals， this may limit detection efficiency. Future designs could reduce cladding thickness to increase area utilization while maintaining low crosstalk， thereby improving overall system performance. In summary， the proposed fiber array method provides a new solution for high-precision tracking of invisible targets and constitutes an important technical step toward all-time space debris laser ranging. With further optimization of fiber parameters， the method offers strong engineering potential and prospects for practical application.

The broad field of view inherent to remote sensing images offers significant advantages for large-scale monitoring tasks， enabling comprehensive surveillance over vast geographical areas with a single acquisition. However， this advantage is often offset by the presence of complex backgrounds， such as cloud cover， shadows， and varying terrain textures， which frequently introduce channel-level noise that interferes with target features. This interference significantly compromises the robustness and reliability of detection models， particularly in adverse weather conditions or densely cluttered environments. Additionally， the substantial variation in target sizes， ranging from small objects like vehicles and helicopters to large structures such as ports and bridges， poses a significant challenge. Detection models struggle to simultaneously capture high-resolution details necessary for identifying small targets and low-resolution semantic information essential for recognizing larger objects， leading to unbalanced detection performance across different scales.

To address the aforementioned challenges， this paper proposes a remote sensing image object detection algorithm based on adaptive feature weighting， built upon the Oriented R-CNN framework. The method introduces two core modules： the Adaptive Channel Weighting Module （ACWM） and the Adaptive Multi-Scale Fusion Pyramid （AMFP）， aimed at tackling background interference and multi-scale target detection issues. The ACWM module is applied after the STAGE 2 and STAGE 3 phases of the feature extraction network to adaptively adjust channel weights， a critical step for enhancing feature representation. By analyzing statistical correlations between channels using the Correlation-Aware Covariance Weighting （CACW） method， it generates dynamic channel weights to enhance target-related features while suppressing background noise and redundant information， balancing the expression of different channels and thereby improving the feature extraction network's ability to extract features from rotated targets. Subsequently， the AMFP module processes the multi-scale features （C2， C3， C4， and C5） extracted by the feature extraction network， employing a hierarchical approach for feature integration. The Multi-scale Perception and Context Integration Module （MPCIM） fuses global semantic features from deep layers with edge and positional details from shallow layers， effectively addressing the issue of small targets being obscured. The Adaptive Layer Weighting Module （ALWM） optimizes the fusion quality of multi-scale features through adaptive layer-wise weighting， enhancing the model's capability to handle diverse target scales ranging from small vehicles to large ports by dynamically adjusting the contribution of each feature level， thus improving adaptability to various target scales. The optimized features （P2， P3， P4， and P5） are then fed into the Oriented RPN and Oriented RCNN head， which， based on the Oriented R-CNN framework， generates high-precision rotated bounding boxes to complete classification and localization tasks.

To validate the effectiveness of the proposed algorithm， extensive experiments were conducted on the DOTA1.0 and DIOR-R datasets. Ablation studies were performed to assess the contributions of the ACWM and AMFP modules. Results indicate that the ACWM module alone improves the mean Average Precision （mAP） by 0.97% on DOTA1.0 and 1.73% on DIOR-R， while the AMFP module contributes an additional 1.30% and 2.01% improvement， respectively. When both modules are combined， the mAP reaches 78.23% on DOTA1.0 and 68.17% on DIOR-R， representing overall enhancements of 2.36% and 3.87% compared to the baseline Oriented R-CNN model. Visualization comparisons further demonstrate the superiority of the proposed method， showing a significant reduction in missed detections and false positives for small targets， particularly in categories such as Small Vehicle， Swimming Pool， Helicopter， and Storage Tank. The method also exhibits improved localization accuracy and better contour fitting for rotated objects， especially in complex backgrounds with varying angles and dense distributions. The experimental results highlight the robustness and adaptability of the proposed algorithm across diverse remote sensing scenarios.

Compared to state-of-the-art methods such as Faster R-CNN， RoI Transformer， and ARC， the proposed approach achieves superior performance in handling small targets and complex orientations， as evidenced by its higher mAP and enhanced visual detection outcomes. However， limitations remain， including potential performance degradation in extremely cluttered scenes or with ultra-small targets， suggesting avenues for future optimization.

In the modern electronic countermeasure environment with strong electromagnetic interference， traditional wireless communication methods such as radio frequency， Wi-Fi， and millimeter waves face challenges like unstable connections and vulnerability to interference or detection. These issues hinder their ability to satisfy the high requirements for stealth and strong anti-interference needed by rear combat formation Unmanned Aerial Vehicles （UAVs）. Ultraviolet Communication （UVC）， with its non-line-of-sight transmission capability， low detectability， and high anti-interference performance in the “solar-blind”band， has become an important means of new-generation covert communication.

In this paper， a joint optimized clustering method （MOPSO-DE） integrating Multi-Objective Particle Swarm Optimization （MOPSO） and Differential Evolution （DE） is proposed to solve the problems of uneven node energy consumption and limited data transmission of traditional clustering algorithms in order to meet the demands for efficient and cooperative communication of formation UAVs in combat missions under UV covert communication.In this paper， we first develop models for UAV inter-copter Ultraviolet （UV） non-line-of-sight communication links and UAV energy consumption. We then propose four key metrics for selecting cluster heads： the node's remaining energy， stability of the UV link's Received Signal Strength Indicator （RSSI）， the node's normalized distance to the leader UAV， and consistency in speed. For the above multi-objective optimization problem， this paper introduces the multi-objective particle swarm optimization algorithm into the cluster head election process， constructs the Pareto optimal solution set by the non-dominated sorting mechanism， and filters out the global optimal cluster head set by combining with the congestion distance strategy， and at the same time introduces the differential evolution mechanism to prevent the algorithm from falling into the local optimum. In the data transmission phase， a communication framework based on the three-layer structure of ‘leader-cluster leader-member’ is designed， and an intra-cluster fast reconfiguration mechanism is proposed to cope with the failure of the cluster leader nodes due to energy depletion， deterioration of the link， or positional deviation. By constructing a single-objective weight function to achieve rapid cluster head replacement without global reclustering， the dynamic adaptive capability and control overhead of the network are effectively improved.

In the simulation validation this paper deploys 100 UAV nodes in a 1 000 m×1 000 m area based on Matlab platform， and comprehensively compares the network performance of MOPSO-DE with five algorithms： LEACH， WCA， LEACH-X， DSWCA， and CNNUC， under different simulation rounds. The results show that MOPSO-DE has significant advantages in terms of node energy consumption， network survival time and data transmission volume. Compared with the LEACH algorithm， WCA algorithm， LEACH-X algorithm， DSWCA algorithm and CNNUC algorithm， the MOPSO-DE algorithm respectively reduced the average energy consumption by 25.8%， 23.6%， 17.1%， 15.3% and 11.1%， and increased the data transmission volume by 91.6%， 54.42%， 29.3%， 12.8% and 9.6%. The article further simulates and analyses the effects of different node numbers， different packet lengths and different node movement speeds on the performance of the algorithm， and the results show that the increase of node density increases the overall communication load of the system； the increase of packet length improves the amount of data transmission per unit of time， but it also significantly accelerates the energy consumption of the nodes； and the effects of different movement speeds on the performance of the network show a ‘pre-favorable， post-favorable’ effect. The impact of different mobile speeds on the network performance shows the stage characteristics of ‘favorable in the early stage and unfavorable in the later stage’.

In summary， the MOPSO-DE multi-objective clustering algorithm proposed in this paper effectively integrates multi-factor optimization strategies and intelligent optimization methods， and achieves significant results in improving clustering efficiency， extending network life cycle， reducing energy consumption and enhancing link robustness， which provides theoretical support and algorithmic basis for the efficient deployment of UAV swarm self-organized communication networks in the future under the complex battlefield environment.

In space-based gravitational wave detection systems， ultra-long laser interferometry arms are established between three communication satellites to detect the gravitational wave， requiring the space telescopes to perform both laser transmission and reception functions. However， the extreme weakness of gravitational wave signals imposes stringent requirements on optical path stability and backward stray light suppression in these telescopes， that is， the backward stray light must be less than 10^-10 of the output laser. The primary source of backward stray light from space telescopes arises from surface scattering. Even in ultra-smooth optical elements （roughness less than 1 nm）， the surface scattering inevitably occurs during laser transmission， generating backward-scattered light that affects the gravitational wave detection. Therefore， precise characterization of ultra-smooth optical surfaces is critical for analyzing and suppressing telescope backward stray light levels. However， conventional non-contact measurement methods face significant challenges， including complex instrument structure， high experimental cost， and insufficient accuracy， making it difficult to achieve rapid and high-precision measurement of ultra-smooth optical surface. Consequently， there is an urgent need to develop a surface quality assessment method for ultra-smooth optical elements to meet the extraordinary precision requirements of gravitational wave space telescopes.

For high-precision scattering measurement of ultra-smooth optical elements， Li B C's team proposed a method based on multi-channel cavity ring down technique. This method obtains the surface scattering rate by analyzing multi-channel ring-down signals， offering advantages including absolute measurement， immunity to laser source intensity fluctuation， and exceptional measurement accuracy. This work further combines the cavity ring-down-based scattering measurement technique with the Generalized Beckmann-Kirchhoff （GBK） scalar scattering model， to establish a method for estimating the surface parameters of ultra-smooth optical elements. In this method， the GBK scattering model is used to establish the scattering rate database of the optical elements， and the scattering rate of the ultra-smooth optical elements at different solid angles is measured based on the cavity ring down technique. Then， the scattering rate distribution measured by cavity ring down method is numerically fitted with the scattering rate database to obtain the surface parameters of the ultra-smooth optical elements， which provides a reference for the scattering characteristics analysis and stray light suppression of the ultra-smooth optical elements of space telescopes.

The scattering rate distribution of ultra-smooth optical element measured by the cavity ring down technique was simulated and calculated， with the measured data numerically fitted through our proposed surface parameter estimation approach. As shown in Figure 3， the fitting achieves remarkable precision with an error of 0.16% and a goodness of fit of 0.999 8. Further evaluation of the method's performance across different parameters demonstrates that within the applicable range of GBK theory， the method can achieve an error of below 4% （typically<0.5%）， while the goodness of fit is greater than 0.96 （often>0.999）. In addition， to address measurement errors induced by scattering overlap during bidirectional beam propagation in standing-wave cavity ring-down experiments， we analyzed key influencing factors. By integrating these findings with our predictive model， we quantified scattering overlap effects at various measurement angles and derived an optimized angular selection scheme to minimize interference.

This work proposes a novel method for estimating surface parameters of ultra-smooth optical elements by combining GBK scalar scattering theory with cavity ring-down scattering measurement techniques. The simulation analysis shows that， within the scope of application of GBK scalar theory， the relative error of this method is less than 4%， and the fitting degree is greater than 0.96， confirming its high accuracy for rapid and precise measurement of surface quality parameters. In addition， aiming at the error caused by the scattering overlap of the back and forth propagation of the beam in the scattering measurement experiment of the standing wave cavity ring down method， we propose a measurement angle selection scheme considering both the signal-to-noise ratio and the measurement accuracy， so as to reduce the influence of the scattering overlap of the forward and backward propagation on the scattering measurement and subsequent surface quality estimation.

The objective of this study is to develop a high-precision optical interferometric phase demodulation method that does not require preset phase shifts and can accurately recover phase information from only three interferograms. The proposed method is designed to overcome the inherent limitations of conventional random phase-shifting algorithms， which typically suffer from large errors， instability， and restricted accuracy improvements， particularly when the number of interference fringes is limited. At the same time， the method ensures robustness under varying fringe types， Signal-to-Noise Ratios （SNR）， and fringe numbers. In this work， a novel three-frame random phase-shifting phase demodulation algorithm is proposed， referred to as the VU&LEF method， which integrates the VU algorithm with ellipse-fitting correction. First， the VU algorithm is applied to three randomly phase-shifted interferograms to extract two orthogonal components of the interferometric signal. In practice， due to noise interference and the limited number of frames， these components are not perfectly orthogonal， and their distribution often forms an ellipse rather than an ideal circle. To correct this deviation， ellipse-fitting is introduced to estimate the ellipse coefficients. A subsequent normalization procedure maps the ellipse into a circle， thereby restoring strict orthogonality between the two components and significantly reducing systematic errors in the subsequent phase calculation. This optimization enables high-precision phase recovery even with only three interferograms， effectively overcoming the main drawbacks of the conventional VU method. To evaluate the performance of the proposed approach， extensive numerical simulations and experimental validations were conducted under diverse conditions. The results demonstrate that the VU&LEF method consistently outperforms the conventional VU algorithm， achieving significantly improved phase accuracy. Even under low-SNR conditions， the proposed method maintains stable phase recovery， whereas the traditional approach exhibits severe degradation. To further assess computational efficiency， the processing time of the VU&LEF method was compared with that of the conventional VU method and the AIA algorithm. Although the ellipse-fitting step introduces a slight additional computational cost， the proposed method remains more efficient than the AIA algorithm while simultaneously offering superior phase accuracy. Furthermore， the robustness of the proposed method was verified using representative open， closed， and complex fringe patterns with significant background fluctuations. The results clearly indicate that the method effectively corrected elliptical distributions into ideal circular forms， thereby reducing measurement errors. In contrast， the conventional VU method exhibited large phase errors and severe distortions in regions with strong background interference， whereas the VU&LEF method substantially mitigated these errors through ellipse correction. Additional tests under varying frame numbers confirmed that the proposed method yields stable and reliable phase recovery with significantly reduced error fluctuations. These findings further indicate that phase correction is indispensable when performing demodulation with only three interferograms， highlighting the wide applicability of the method in practical interferometric measurements. From an application perspective， requiring only three interferograms greatly reduces data acquisition time compared with conventional multi-frame methods. The additional computational cost introduced by ellipse-fitting correction is negligible compared with the measurement time saved. This combination of high efficiency and accuracy makes the method particularly suitable for real-time and high-speed measurement scenarios， such as dynamic surface profiling， deformation monitoring， in-situ industrial inspection， and other precision optical metrology tasks. In conclusion， the proposed three-frame random phase-shifting phase demodulation method with ellipse-fitting correction does not require the phase shifts of interferograms to be predefined or equally spaced， and thus constitutes a true random phase-shifting technique. It inherits the advantage of the VU method in not requiring prior calibration of phase steps， while enabling high-precision phase recovery from minimal data. Moreover， it demonstrates strong robustness against noise， fringe variability， and complex background interference. Both simulation and experimental results verify that the proposed method outperforms conventional approaches in terms of accuracy， stability， and computational efficiency.