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01 October 2025, Volume 45 Issue 5 Previous Issue   

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Review and perspective of spectroscopic technology for life signal detection on habitable planets ZHANG Qihang, ZHANG Naixin, OUYANG Yixin, LONG Xiyang, HOU Xinlan, ZHANG Xiaojing, LIU Jilin, HUO Zhuoxi, TIAN Yuxi 2025, 45 (5):  1-13.  doi: 10.16708/j.cnki.1000-758X.2025.0071 Abstract ( 19 )   PDF (5674KB) ( 1 )   Save Spectroscopy, as an important analytical tool, is widely applied in the detection of biosignatures and the assessment of planetary habitability. This review summarizes recent advances in spectroscopic techniques for detecting habitable exoplanets and biosignature molecules: First, it introduces the spectroscopic characteristics of common small-molecule biomarker gases indicative of life on habitable planets. Then, it describes the infrared spectroscopic precision measurement techniques, and discusses the influence of environmental factors on molecular infrared spectroscopy. Next, it elaborates on the progress in molecular spectroscopic detection technologies for studying interstellar and atmospheric molecules. Finally, it describes the potential of spectroscopy in the search for life on exoplanets, discussing the prospective applications of ground-based spectral simulation facilities and artificial intelligence technologies in advanced spectral detection of life beyond the Earth. Related Articles | Metrics

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Physics-informed deep learning for molecular spectrum GAO Baoquan, QUAN Donghui, HU Jianping, PAN Yijun 2025, 45 (5):  14-21.  doi: 10.16708/j.cnki.1000-758X.2025.0072 Abstract ( 10 )   PDF (2919KB) ( 1 )   Save Accurate modeling of mid-infrared vibrational-rotational transition spectra is pivotal for detecting biosignatures and prebiotic molecules in exoplanetary atmospheres. Conventional line-by-line radiative transfer methods encounter prohibitive computational costs when generating high-resolution spectra across extensive parameter spaces, particularly limiting real-time atmospheric retrieval and large-scale exoplanet surveys. To address these challenges, a physics-informed deep learning framework was developed for rapid and precise spectral generation. The architecture incorporates three key components: A parameter-encoding layer establishing global correlations between temperature-pressure conditions and spectral line parameters; Multi-head self-attention mechanisms capturing long-range dependencies in vibrational-rotational features; A physics-constrained decoder incorporating residual modules derived from line profile equations to minimize non-physical deviations. The framework demonstrated successful reconstruction of molecular absorption cross-sections from the HITRAN database at 0.01cm－1 resolution, achieving a 100× acceleration compared to conventional HAPI simulations while maintaining spectral fidelity. The framework accurately preserved fundamental spectroscopic principles, including line intensity scaling and rotational temperature dependencies, across diverse atmospheric conditions. This approach represents the first integration of spectroscopic constraints into neural network-based spectral generation, enabling interpretable temperature-pressure-spectral correlations and compatibility with photochemical network- driven biosignature assessments. The method now provides a computationally efficient solution for next-generation spectral databases, significantly advancing molecular characterization of exoplanetary environments and enhancing biosignature detection systems through photochemical network integration. Related Articles | Metrics

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Knowledge-constrained deep learning model for predicting astrochemical reactions ZHANG Yanan, YANG Peilun, WANG Jiawei, BU Haili, DUAN Manni, QUAN Donghui 2025, 45 (5):  22-32.  doi: 10.16708/j.cnki.1000-758X.2025.0073 Abstract ( 7 )   PDF (6686KB) ( 1 )   Save In astrochemical research, analyzing the evolutionary processes of species within astrophysical regions requires reconstructing their reaction pathways under dynamic physical conditions. This process heavily relies on an accurate and comprehensive astrochemical reaction network. Traditional methods for constructing such networks primarily depend on expert knowledge and experimental validation to identify chemical reactions between species, which entails high time and computational costs. In this context, a deep learningbased predictive method named GraSSCoL-2 is proposed to enable efficient prediction of astrochemical reactions, thereby accelerating the analysis of species evolution.GraSSCoL-2 incorporates a graph encoder, a sequence decoder, and contrastive learning techniques. Trained on existing reaction data, it can effectively predict both forward and reverse reaction pathways among astrochemical species. Evaluated on Chemiverse, a state-of-the-art astrochemical reaction dataset, GraSSCoL-2 achieves Top-1, Top-3, Top-5 and Top-10 accuracies of 81.8%, 91.3%, 92.9% and 93.4%, respectively, for forward reaction prediction, representing relative improvements of 3.5%, 3.6%, 2.9% and 2.5%. For reverse reaction prediction, the corresponding accuracies are 76.2%, 87.6%, 89.9% and 90.5%, with relative gains of 1.9%, 1.8%, 1.8% and 1.2%. Furthermore, experimental results indicate that the combined application of SMILES augmentation and hydrogenation strategies significantly enhances prediction accuracy. Additionally, the proportion of invalid SMILES generated in forward and reverse reaction prediction tasks is 3.0% and 3.9%, respectively, a substantial reduction from 14.2% and 14.6% observed with GraSSCoL. These findings demonstrate that GraSSCoL-2 not only ensures high prediction accuracy but also significantly improves the validity of generated results, further validating its reliability and applicability in astrochemical reaction prediction tasks. Related Articles | Metrics

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The principle of exoplanet detection：optical stellar interferometry HU Chenyu, LIU Huigen, ZHANG Lijian 2025, 45 (5):  33-48.  doi: 10.16708/j.cnki.1000-758X.2025.0074 Abstract ( 9 )   PDF (4598KB) ( 2 )   Save Exoplanet detection is a key frontier in modern astronomy. The fundamental principles of optical stellar interferometry are systematically reviewed and its application in resolving exoplanetary systems with extremely small angular separations and ultra-high brightness contrasts is explored. Its potential for exoplanet detection and super-resolution imaging through the framework of quantum information theory is further assessd. Building on classical optical coherence theory, the core principles of stellar interferometry and its ability to resolve binary point sources and complex astrophysical structures are analyzed. By incorporating quantum information theory and parameter estimation techniques, the problem of exoplanetary system resolution is revisited and the advantages of quantum-inspired interferometric techniques are quantified in achieving super-resolution imaging. Optical stellar interferometry, leveraging multiple telescopes and synthetic apertures, surpasses the diffraction limit of single telescopes, enabling high-resolution, high-contrast astronomical imaging. Specialized configurations, such as nulling and phase-referenced interferometry, offer significant advantages for imaging exoplanetary systems with extreme brightness contrasts. Quantum-inspired interferometry, guided by quantum information theory and parameter estimation, has the potential to exceed classical resolution limits, reaching the quantum limit for resolving binary point sources and measuring angular distances. Optical stellar interferometry enables high-resolution imaging of exoplanetary systems with extreme brightness contrasts through long-baseline arrays and advanced configurations. The proposed approach achieves the quantum limit for resolving exoplanetary systems and measuring angular distances, surpassing the classical constraints of direct intensity measurements and demonstrating its potential for super-resolution imaging. Related Articles | Metrics

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Dual-branch GAN for cloud image generation based on cloud and background decoupling LI Junyong, CHEN Keyan, LIU Liqin, ZOU Zhengxia, SHI Zhenwei 2025, 45 (5):  49-59.  doi: 10.16708/j.cnki.1000-758X.2025.0075 Abstract ( 7 )   PDF (12351KB) ( 1 )   Save Cloud image generation is an important branch of remote sensing image generation. Nevertheless, prevailing approaches predominantly target the production of homogeneous cloud types, offering inadequate control over cloud coverage and opacity. Furthermore, the failure to disentangle cloud attributes and terrestrial features seriously affect the diversity and veracity of the generated cloud images, which cannot meet the simulation requirements.This research introduces DecoupleGAN, a bifurcated GAN framework for cloud image generation based on the decoupling of cloud and background. DecoupleGAN employes a pair of separate GANs to independently capture the characteristic representations of cloud formations and the underlying background. Leveraging a cloud-s with remote sensing backdrops, extracting features with heightened efficiency and no cross-interference, thereby culminating in superior quality cloud imageries. Complementarily, this study also introduces a dataset comprised of varying cloud coverage categories, broadening the generative scope of the model. The algorithm has been verified to exhibit superior performance in simulation, specifically with an FID value of 49.0012 and a KID value of 0.0253, representing performance improvements of 33.11% and 16.98% respectively compared with single-branch networks. Moreover, compared with existing cloud generation methods, this algorithm can generate more realistic and diverse types of clouds, and is capable of simultaneously generating multiple different types of land cover backgrounds, significantly expanding the scope of application and practicality. DecoupleGAN achieves more realistic and harmonious cloud image simulation effects by decoupling the clouds from the background and independently processing the two branches, effectively preventing interference during the feature learning process. Related Articles | Metrics

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Object tracking in satellite videos: a survey LI Yangfan, LI Wei, TIAN Jing, SHEN Qing 2025, 45 (5):  60-74.  doi: 10.16708/j.cnki.1000-758X.2025.0076 Abstract ( 7 )   PDF (4775KB) ( 1 )   Save This paper aims to review the research progress in remote sensing satellite video single-target tracking technologies, analyze the advantages and disadvantages of existing methods, and explore future development directions. Through literature review and comparative analysis, the research achievements in this field over the past five years were systematically summarized. The existing methods are categorized into two types： correlation filtering-based methods and deep learning-based methods. The technical features and performance of each category were analyzed. Tracking accuracy of representative methods was evaluated based on publicly available datasets, and the applicability and limitations of different methods were discussed. Experimental results show that correlation filtering-based methods perform excellently in terms of computation speed and tracking accuracy. On the publicly available SatSOT dataset, the highest tracking accuracy can reach 69.8%, with an average frame rate exceeding 30frame/s, demonstrating strong practicality and real-time performance. These methods efficiently track targets with low computationalcost by utilizing appearance features and motion information, making them particularly suitable for resource-constrained onboard platforms. In contrast, deep learning-based methods have significant advantages in feature representation and adaptability to complex scenes, but due to the lack of large-scale annotated data in the remote sensing domain, their highest tracking accuracy on the SatSOT dataset is currently 66.9%, slightly lower than correlation filtering methods. This paper summarizes the research progress in remote sensing satellite video single-target tracking. Correlation filtering methods are mature and highly real-time, suitable for current tasks. Deep learning methods show great potential but require further improvements in model optimization. Related Articles | Metrics

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Surface reconstruction techniques for asteroid missions and the applications in autonomous optical navigation TIAN Qihang, LIU Yiwu, WANG Li, YAN Sichang, LIN Dayong, HUA Baocheng, LIANG Xiao 2025, 45 (5):  75-90.  doi: 10.16708/j.cnki.1000-758X.2025.0098 Abstract ( 30 )   PDF (10036KB) ( 13 )   Save Autonomous optical navigation (OpNav) is expected to play a crucial role to aid in the in-situ determination of spacecraft trajectory. For asteroid missions, the high communication latency with Earth makes feedback guidance intractable and limited in capabilities. The situation becomes worse in the case of constrained uplink bandwidth and unknown physical properties of the target body. Therefore, the significance of an onboard target-relative navigation system is axiomatic. In this work, a novel and feasible framework of visual imagery-based measurements is proposed in support of the upcoming planetary missions. The framework consists of two segments: ground support system (GSS) and onboard feature recognition system (OFRS). In GSS, structure from motion and stereophotoclinometry are integrated for developing topographic models of both entire body and surface areas as navigation features at different image resolutions. OFRS works by rendering the expected appearance of the uploaded feature catalog, which is registered to the onboard collected image. The corrected bearing measurement can then be fed to navigation filter to update the onboard spacecraft knowledge. The application of ICQ model is first proposed for on-orbit extended-body centroid tracking. The amount of data uploaded is only 20% of the conventional model, and the pointing measurement accuracy of 3% of the target diameter in pixels can be achieved. The masked NCC technique was first applied to implement on-orbit feature recognition. It is demonstrated that the computation of masked NCC registration is as accurate as that of the standard NCC registration, while the efficiency can be improved by about 1 order of magnitude. This work describes the principle and performance of the framework, with examples from the previous small body asteroid mission and simulations. The proposed framework enables autonomous and efficient localization of spacecraft.  Related Articles | Metrics

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Research on the navigation constellation of the Lunar South Pole GAO Weiguang, LI Gang, WANG Shen, LIU Yingchun, WU Guoqiang 2025, 45 (5):  91-100.  doi: 10.16708/j.cnki.1000-758X.2025.0077 Abstract ( 11 )   PDF (7867KB) ( 4 )   Save The configuration of the Lunar South Pole satellite navigation constellation is studied. Comparing the dynamic characteristics of the lunar orbit and the three body orbit, a hybrid heterogeneous constellation mainly composed of NRHO (Near-rectilinear Halo Orbit) and ELFO (Elliptical Lunar Frozen Orbit) is proposed to support Lunar South Pole navigation. A dual optimization objective function of constellation value and total costs is constructed, with the number of satellites in different orbits and ELFO satellite orbit parameters as decision variables. The NSGA-Ⅱ (Non-dominated Sorting Genetic Algorithm Ⅱ) algorithm is used to optimize the configuration design of the Lunar South Pole navigation constellation. The simulation results show that a Lunar South Pole constellation configuration of 2 NRHO and 4 ELFO satellites can achieve CV value of 95% and a positioning accuracy of 50m. The relevant results can provide reference for the research and engineering application of Lunar South Pole navigation constellation in the future. Related Articles | Metrics

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Optimization of regional remote sensing satellite constellation based on improved crayfish algorithm HE Zhiqian, KANG Huifeng, XIA Guangqing, ZHOU He 2025, 45 (5):  101-109.  doi: 10.16708/j.cnki.1000-758X.2025.0078 Abstract ( 6 )   PDF (5037KB) ( 1 )   Save In response to the problem of trade-offs between coverage performance and constellation cost in the design of regional remote sensing satellite constellations, a constellation model with a short average revisit time and the minimum number of satellites as the objective function was established by utilizing the characteristics of regional coverage satellite constellations and the Walker constellation. The optimization variables involved include satellite orbit altitude, inclination, number of orbital planes, and number of satellites per orbital plane. Aiming at the shortcomings of traditional algorithms for solving the satellite constellation optimization problem, such as slow convergence speed and easy fall into local optimization, an improved crayfish optimization algorithm IMOCOA (Improved Multi-objective Crayfish Optimization Algorithm) is proposed, and the IMOCOA algorithm incorporates the refractive inverse learning strategy into The IMOCOA algorithm incorporates the refractive inverse learning strategy into the population initialization process to achieve a more uniform distribution of individuals in the solution, as well as the strategy of introducing a nonlinear convergence factor in the position update to enhance the global optimization search capability. The evaluation results of the ZDT (Zitzler-Deb-Thiele) series of multi-objective test functions in terms of both convergence and diversity show that the IMOCOA algorithm outperforms the NSGA-2, MOPSO, and MSSA algorithms. Its optimality metrics on IGD, GD, and HV, as well as SP, are improved over the other three algorithms by 54.4%, 78.7%, respectively, 3.6% and 27.3%, verifying the advantages of IMOCOA algorithm over the other three algorithms in convergence speed, convergence stability and diversity. The IMOCOA algorithm is used in the optimization design of a remote sensing satellite constellation in the Beijing-Tianjin-Hebei region to solve the problem of the minimum number of satellites under the requirement of revisit time. The simulation results show that the selection of three satellites can achieve an average revisit coverage of the Beijing-Tianjin-Hebei region of 1.54h, which further verifies the validity of the IMOCOA algorithm in solving this kind of problem. Given the problem of long simulation time, the introduction of reinforcement learning can be considered in future work to train and predict the model, to improve the optimization efficiency, and at the same time, the regional constellation design method based on the improved crayfish optimization algorithm can be used as a reference for the future construction of low-orbit constellations. Related Articles | Metrics

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Whole-process optimal trajectory design and real-time control for hopping detection mission YU Ping, WANG Haofan, WANG Zeguo, FU Renhao 2025, 45 (5):  110-120.  doi: 10.16708/j.cnki.1000-758X.2025.0079 Abstract ( 3 )   PDF (5552KB) ( 1 )   Save The hopping detection is a novel form of extraterrestrial body exploration mission, which is a combination of ascent missions and landing missions. The study of control methods that combine the entire process of hopping trajectory optimization and real-time performance is of great significance. In terms of nominal trajectory optimization, unlike traditional segmented optimization methods, a trajectory design method that combines analytical and partial differential approaches is proposed from the perspective of optimizing the entire hopping process. In terms of real-time trajectory control, based on the prediction-correction method, the Jacobian matrix is applied to ensure the achievement of terminal conditions by comprehensively correcting trajectory parameters and thrust directions. The calculation formulas for the Jacobian matrix used in real-time trajectory control are all explicit and analytical, and simulations show that only two iterations are enough to meet control requirements, proving that the algorithm proposed has high real-time performance. With the same simulation conditions, compared with the offline whole-process convex optimization results, the consumed fuel difference between the two methods is only 20g, indicating that its fuel optimization performance is relatively similar to the convex optimization one. This method can be applied to the whole-process thrust hopping trajectory optimization with constant thrust and real-time trajectory control, ensuring the whole-process optimality and real-time control performance. Related Articles | Metrics

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A torque distribution algorithm considering momentum envelope of reaction-wheel arrays for spacecraft attitude maneuver LEI Yongjun, LIU Jie, YUAN Li 2025, 45 (5):  121-131.  doi: 10.16708/j.cnki.1000-758X.2025.0080 Abstract ( 4 )   PDF (4767KB) ( 1 )   Save The torque/angular momentum saturation due to the output limitation of the reaction wheel is adverse to the attitude maneuver performance of the spacecraft. To deal with this problem, torque distribution and angular momentum management is investigated for the spacecraft with a redundant reaction wheel array. Firstly, according to the inertia parameters and the expected maneuver direction of the spacecraft, angular momenta of reaction wheels and the maximum spacecraft slew angular rate are determined from the system momentum at the intersection of the angular momentum envelope along its varying direction．Secondly, the maximum slew torque available is derived by use of the desired angular momentum rate, which is devised to be in proportion to the variation of the angular momentum with its L∞-norm satisfying the torque constraint. Then, a novel torque distribution algorithm is developed by minimizing a quadratic function of the deviation between the angular momentum varying rate and its expected value, making the angular momentum envelope accessible. Finally, numerical simulations are executed with the proposed scheme as well as the L2 and L∞ torque distribution methods when the same maneuver torque requirement is provided. By the selection of the maximum angular rate/acceleration and the torque distribution law, the attitude maneuver in an arbitrary direction can be achieved to the best of ability, significantly improving the agility and autonomy of the spacecraft. Related Articles | Metrics

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Real time pose measurement of space non-cooperative targets at ultra-close range based on ICP algorithm ZHAO Hanxue, HU Jiaqian, SHAO Changbao, JIANG Haitian, LI Shuang 2025, 45 (5):  132-142.  doi: 10.16708/j.cnki.1000-758X.2025.0081 Abstract ( 3 )   PDF (7450KB) ( 1 )   Save To address the limitations of traditional methods in meeting the real-time and high-precision requirements for ultra-close-range pose measurement tasks, this paper proposes a ultra-close-range real-time pose measurement method of space non-cooperative target based on the Iterative Closest Point (ICP) algorithm. The proposed approach integrates high-precision pose estimation for keyframes with real-time pose tracking for non-keyframes. Initially, statistical filtering was applied to keyframes for point cloud denoising to enhance computational efficiency. The point cloud was then sparsified using a downsampling method based on the centroid of neighboring points within the voxel grid. Subsequently, a combination of coarse registration and ICP was employed to determine the pose of keyframes relative to the target model, thus achieving pose estimation for keyframes. For non-keyframes, uniform downsampling coupled with ICP was used to capture real-time pose changes between consecutive non-keyframes, facilitating pose tracking. Finally, the real-time pose tracking of non-keyframes was fused with pose estimation of keyframes to eliminate the cumulative errors and obtain high-precision, real-time pose measurements. Simulation results demonstrate that the proposed algorithm can achieve real-time pose measurement for close-range non-cooperative targets and its computational frequency can reach 24Hz, with an attitude error of no more than 1° and a position error within 2centimeters. These findings suggest that the proposed algorithm, designed with novel architectures based on the traditional ICP method, achieves high-precision pose estimation for keyframes and real-time position tracking for non-keyframes. The accumulative error of real-time pose tracking is suppressed by fusing high-precision pose estimation. This approach ensures real-time performance while meeting the high-precision requirements of ultra-close-range measurement tasks involving non-cooperative targets. Related Articles | Metrics

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Energetic proton radiation effects on the super large array 9k×9k CCDs used in a space telescope WANG Zujun, WANG Xiaodong, YANG Ye, TANG Ning, YAN Shixing, LIU Changju, GUO Xiaoqiang, SHENG Jiangkun, GOU Shilong, LYU Wei, YE Wenbo, WANG Zhongming 2025, 45 (5):  143-149.  doi: 10.16708/j.cnki.1000-758X.2025.0082 Abstract ( 8 )   PDF (5082KB) ( 2 )   Save To know about the radiation effects on the super large array 9k×9k CCDs used in a space telescope induced by energetic protons, the experiments of the super large array 9k×9k charge coupled devices (CCDs) used in the space telescope irradiated by 60MeV and 100MeV protons are presented. The samples were exposed by 60MeV and 100MeV protons at fluences of 5×109 /cm2 and 1×1010 /cm2, respectively. The degradations of the main performance parameters of the super large array CCDs which are paid special attention to the space telescope are investigated. The full well capacity, mean dark current, and the charge transfer inefficiency (CTI) versus proton fluence are presented, which are tested at very low temperature of -85℃. The annealing tests of 168h were carried out after proton irradiation. The dark images before and after proton irradiation are also presented to compare the image degradation. The degradation mechanisms of the super large array CCDs irradiated by protons are analyzed. The experimental results show that the main performance parameters of the CCDs are degraded after 60 MeV and 100 MeV protons and the degradations induced by 60MeV protons are larger than that induced by 100MeV protons. The experimental results of the super large array CCDs irradiated by protons will provide the basic test data support for orbit life assessment of the space telescope. Related Articles | Metrics

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Theoretical analysis of the effect of pore size of wick on loop heat pipes for space application LIN Bingyao, LI Nanxi, JIANG Zhenhua, YAN Zhe, WU Yinong 2025, 45 (5):  150-159.  doi: 10.16708/j.cnki.1000-758X.2025.0052 Abstract ( 58 )   PDF (6544KB) ( 6 )   Save The wicks are the power component of the loop heat pipes, and the pore size of the wick determines the evaporation heat transfer and capillary force that the wick can provide. Therefore, in order to analyze the influence of the pore size of the wicks on the loop heat pipes, the cylindrical microchannel thin film evaporation model was established by using the augmented Young-Laplace formula and the theory of energy conservation, and the theory was applied to the performance analysis of the loop heat pipe evaporator. At the same time, in order to obtain the experimental data of the effect of wicks pore size on the performance of loop heat pipes, two copper-propylene loop heat pipes with different wicks pore sizes were prepared, and their heat transfer performance was tested under vacuum environment under the heating load from 10 to 30W. Combined with the experimental data and the above model, the loop heat pipe is analyzed, and the results show that the heat transfer performance of the evaporator is affected by the heat transfer quantity and heat transfer coefficient of the wick, and the growth rate of the evaporative heat transfer coefficient slows down with the increase of the heating load, and the heat transfer performance of the evaporator deteriorates when the heating load exceeds the critical heat flux. Related Articles | Metrics

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Sputtering mechanism of C55 wire insulation materials by electric-propulsion plasma YU Bo, DENG Ruonan, ZHANG Guangchuan, ZHANG Yan 2025, 45 (5):  160-169.  Abstract ( 2 )   PDF (8404KB) ( 1 )   Save The impact of the electric-propulsion plasma sputtering onto the insulation layer of C55 wire has exerted a great significance on the spacecraft safety, and the conductor with damaged insulation layer can cause short circuit of gas breakdown or between conductors. These impacts seriously reduce the reliability of the on-orbit operation for aircraft. In order to study the relevant sputtering mechanism, a sputtering test of polytetrafluoroethylene (C55 wire insulation material) by Xe plasma is conducted. Specifically, the quartz crystal microbalance (QCM) is employed to measure the solid sputtering yield of the target, the electronic weighing balance is employed to measure the total sputtering yield of the target, and the field emission scanning electron microscope is used to measure the element composition of the QCM surface collection and the exhaust gas of the vacuum chamber. Based on the above measurement data and its variation rule, the sputtering products and relevant mechanism of Xe plasma on polytetrafluoroethylene is deduced. The results show that, as the incident energy of ions increasing, different sputtering products can be generated, that only -［CF2］- long-chains (solid state) is generated with the incident energy less than 10eV, and that both the -［CF2］- short-chains and the -［CF2］- long-chains are generated. During the entire increase in incident energy, the sputtering yield of solid objects first increases, then decreases, and then increases again, and this trend is probably related to the different monotonicity between the long-chain -［CF2］- detachment velocity and cleavage velocity. The present study reveals the plasma-polytetrafluoroethylene sputtering mechanism that has a high correlation with the sputtering products and conducts a remarkable influence on the sputtering yield.Finally, this study can provide the theoretical foundation for the subsequent research of plasma-polytetrafluoroethylene sputtering yield simulation model. Related Articles | Metrics

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An interrupted sampling repeater jamming suppression algorithm in complex scenarios WANG Linxi, WEI Zhen, HUI Zheng 2025, 45 (5):  170-182.  doi: 10.16708/j.cnki.1000-758X.2025.0084 Abstract ( 3 )   PDF (13009KB) ( 1 )   Save Interrupted sampling repeater jamming(ISRJ) is a very threatening intra-pulse forwarding interference faced by radar systems in recent years. Through interrupted sampling and time-sharing forwarding technology, the jammer repeats the process of "intercept-slice-forward" in the jamming period. The sampling, storage and forwarding of intercepted radar signals can produce multiple false targets in the current repetition period, and the interference amplitude is strong, which seriously affects the radar's detection and tracking level of targets. Therefore, ISRJ suppression technology has become a research hotspot in the field of radar countermeasures.An improved ISRJ suppression algorithm based on time-frequency analysis is proposed for the complex scenario of "multi-interference & strong and weak interference coexistence". Firstly, the time-domain duty cycle of jamming is reduced by dechirp and time-domain alignment; secondly, the impact of noise is further reduced by time-frequency image binarization and thedetection probability of target and jamming is improved; then, target components are eliminated according to the cumulative characteristics of short-time Fourier time-frequency analysis in the time dimension, and the corresponding bandpass filter is designed to remove ISRJ; finally, the target signal is reconstructed by recovering the slope of the dechirped target echo. In addition, a number of simulation experiments are conducted to verify the effectiveness and robustness of the proposed algorithm under different SNR and different intensity combined ISRJ scenarios. Two existing classical algorithms are used as control groups to compare and verify the superior jamming suppression performance of the proposed algorithm.Simulation results show that the proposed algorithm can adapt to different SNR, and the jamming suppression ability is obviously better than the two control algorithms, and both remain at a high level. With the increase of SNR, jamming suppression performance of the proposed algorithm is also gradually improved. The proposed algorithm can adapt to the jamming of different intensity combinations, especially in the scene containing weak jamming, through the analysis and processing of time-frequency domin, the weak jamming components are effectively eliminated, and the improvement factor of the SIR is greatly improved.The proposed algorithm has good practicability for ISRJ suppression, and provides an important reference for the subsequent reconnaissance and jamming system design in the field of wide and narrow band radar countermeasures. It is of great significance for improving radar detection efficiency and grasping information control dominance in complex electromagnetic environment. Related Articles | Metrics

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A trusted satellite access and transmission mechanism based on verification technology DING Yi, WANG Yang, GUO Wenxin, CHENG Zijing, LI Jie, JIN Jun 2025, 45 (5):  183-196.  doi: 10.16708/j.cnki.1000-758X.2025.0069 Abstract ( 51 )   PDF (13911KB) ( 28 )   Save Satellite communication is an indispensable part of modern communication network， and its trustworthiness is essential to ensure the reliable and accurate transmission. This paper proposes a trusted satellite access and data transmission mechanism， aiming at the area of channel resource allocation and the transmission of critical information within satellite communication system. Firstly， to address the challenge of trust related to channel allocation caused by the scarcity of satellite resources， a verification model for the execution of channel allocation policy is constructed based on verifiable technology to verify whether the policy is executed correctly. Secondly， to mitigate the risks of tampering and attacks during the transmission of vital information such as remote sensing images and navigation data， a verifiable data transmission model is designed by using the methods of verifiable technology， encryption and distributed secure transmission， etc., thereby enhancing the integrity and authenticity of the transmitted data. On the basis of these models， instance designs for satellite communication system are explored： a satellite channel allocation system and a secure satellite data transmission system. The former ensures openness， transparency and verifiability of the channel allocation， while the latter ensures the security and accuracy of data transmission. Security analysis and experimental results show that the proposed mechanism can effectively detect such threats as policy tampering， data eavesdropping， and spoofing attacks， with only minimal computational overhead. The mechanism meets the dual requirements of security and efficiency in practical applications， providing both theoretical support and practical demonstration for building a trusted satellite communication network. Related Articles | Metrics