Exoplanet detection technologies are undergoing a systematic transition from ground-based observations to space-based platforms, and from large-scale planet discovery to detailed physical and atmospheric characterization. This paper presents a comprehensive review of the principles and current status of the major exoplanet detection techniques, including transit photometry, radial velocity measurements, as well as direct imaging and interferometric observations. The applicability and technical limitations of different observational approaches are compared in terms of planet detection, orbital determination and atmospheric characterization. Recent progress of representative space missions currently in operation or under development worldwide is summarized. The review shows that indirect detection methods continue to dominate in terms of the number of discovered exoplanets, providing essential statistical foundations for studies of planetary occurrence rates, population properties, and formation and evolution processes. Meanwhile, direct detection techniques, enabled by advances in adaptive optics, coronagraphy, and optical interferometry, have achieved significant breakthroughs in high-contrast imaging and atmospheric spectral retrieval of exoplanets. Infrared imaging missions represented by the James Webb space telescope have enabled direct multi-band spectroscopic measurements of exoplanetary atmospheres, while the development of ESA's LIFE mission and China's MEAYIN project marks the entry of space-based infrared interferometric detection into a new phase of ultra-high angular resolution. Future exoplanet exploration is expected to establish a coordinated framework that integrates ground-based and space-based observations as well as complementary indirect and direct detection techniques, thereby laying a solid scientific and engineering foundation for the detection of habitable planets and potential biosignatures.

The Moon harbors abundant critical mineral resources, including water ice,ilmenite and helium-3 (³He). Exploiting these resources holds significant strategic value for sustaining deep-space exploration missions, addressing future resource scarcity, and catalyzing new space-based economic models. This study introduces the reserves and occurrence characteristics of key lunar mineral resources such as water ice, solid minerals, and ³He. It identifies major challenges in lunar resource utilization, including the harsh extreme lunar environment, uncertainty in resource distribution, limitations of energy supply systems, and reliability of robotic equipment. Based on this, the study reviews research progress in the utilization technologies of key lunar mineral resources, summarizes the full-process technological system for lunar resource development and utilization, and puts forward development suggestions in areas such as interdisciplinary talent development, exploitation strategies, technical verification, feasibility studies, policies and regulations, and international cooperation models.

Communication satellites, as the pivotal core of satellite communication systems, are instrumental in shaping the architecture of next-generation communication networks and advancing the aerospace industry. This paper provides an overview of the current state of international communication satellite system. It systematically summarizes the technological innovations and applications of China's civil and commercial communication satellites over the past decade. Furthermore, the paper analyzes the technological gaps between China and other nations in key areas such as high-throughput satellites (HTS), direct-to-cell satellite technology, and satellite internet. A developmental framework centered on "collaborative networking, space-ground integration, and intelligent management and control" is proposed. Finally, core future directions and technologies for China's communication satellite development are identified, including multi-orbit (GEO/MEO/LEO) collaborative networking, integrated space-ground communication networks, intelligent dynamic resource management, ultra-high-capacity fully flexible communication, and highly integrated intelligent platforms. This work aims to provide strategic support for the development of China's new generation of communication satellites and the construction of an integrated space-ground communication network.

With the widespread application of Global Navigation Satellite System (GNSS) and the continuous emergence of new navigation and timing technologies, GNSS development and applications have entered a new stage internationally since 2020. While various countries are strengthening research on the integration of GNSS with other PNT technologies, they are also placing greater emphasis on system innovation as well as improvements in accuracy, continuity, integrity, and security to make GNSS the core of comprehensive PNT architectures. Based on a systematic review of the achievements in the construction of foreign GNSS and China’s BeiDou navigation satellite system (BDS), development trends for satellite navigation systems are investigated and summarized. In accordance with the requirements for building an integrated PNT architecture centered on satellite navigation, the new needs of GNSS users and the missions of new BeiDou satellites are analyzed. Finally, key technologies that should be prioritized are proposed for research, aiming to provide support for advancing satellite navigation technologies and build a BeiDou system featuring “more advanced technologies, stronger capabilities, and higher-quality services”.

With the advancement of deep space exploration, extraterrestrial objects exploration has become a strategic focus of space programs worldwide. Autonomous mobile operation robots, as key platforms for scientific exploration and resource utilization, face dual challenges posed by complex environments and diversified mission requirements. A systematic review was conducted of the characteristics of extraterrestrial objects and current mission, and three key technologies were identified: high-performance mobility control over rugged terrain, localization and navigation based on multi-source perception, and swarm robots control for collaborative tasks. Recent research progress was analyzed to outline future trends. Firstly, recent progress in rugged-terrain mobility for wheeled and legged systems was reviewed, with an ongoing shift identified from generalized passive adaptation toward task-oriented structural innovation and intelligent control. Secondly, advances in SLAM and intelligent path planning were surveyed, highlighting the complementary value of visual and LiDAR sensing. A clear transition in research focus was reported, moving from environmental geometric reconstruction to semantic scene understanding, which is essential for autonomous cognition and decision-making in unknown, dynamic environments. In swarm robot control, centralized, distributed, and hybrid control architectures were compared. The hybrid architecture was identified as the future direction for optimally balancing system efficiency and robustness. Finally, from the perspectives of structural optimization, intelligent autonomous decision-making, and swarm architectures, development recommendations for future extraterrestrial objects autonomous mobile operation robots were proposed.

As the “fifth airspace” bridging near space and outer space, the Ultra Low Earth Orbit (ULEO) domain boasts comprehensive advantages unmatched by traditional orbits in ultra-high-resolution remote sensing, low-latency high-signal-to-noise-ratio communication, and civilian emergency backup services for public livelihood, making it a frontier field prioritized by major space powers. However, constrained by unique challenges such as significant atmospheric drag and severe environmental disturbances, ULEO satellites currently face the core bottlenecks of being “difficult to sustain, difficult to stabilize, and difficult to fully utilize.” Targeting the requirements of long-term operational applications, this paper systematically reviews the key technology systems and development pathways for ULEO spacecraft. First, in terms of environmental awareness, multi-modal environmental detection techniques and methods for constructing high-precision atmospheric models are discussed. Second, in terms of platform technology, the analysis focuses on advanced propulsion systems centered on air-breathing electric propulsion, aerodynamic simulation and drag reduction design, intelligent orbit and attitude control strategies addressing strong time-varying nonlinear disturbances, as well as high-flux atomic oxygen protection technologies. Additionally, in terms of payload and information processing, the current development status of low-latency communication, sub-target-level high-resolution remote sensing payloads, and onboard information processing technologies adapted to the ULEO environment is elaborated. Finally, analysis shows that ULEO development urgently needs to bridge the gap from simulation verification to engineering application. Future efforts should focus on key technology breakthroughs such as the development of air-breathing electric propulsion prototypes, integrated aerodynamic drag reduction design, high-precision attitude and orbit control, and onorbit flight verification, to support the construction and application of next-generation space-based systems.

Robotic on-orbit servicing is an emerging trend. However, space missions often involve unstructured scenarios with targets and environments of irregular physical properties. Traditional methods rely on external aids like markers to structure the scene, which incurs high costs, complex deployment, and poor robustness. This study aimed to develop robotic manipulation technology for the above mentioned unstructured environments. The authors designed an architecture supporting diverse inputs. The embodied perception module integrated vision-language models and zero-shot learning for unstructured perception. The dexterous manipulation module combined dynamic pose servoing with a two-stage compliance control for fine manipulation. This integration enabled intelligent target perception and flexible skill application without complex scene modification. In a typical power drill operation scenario, an arm-hand robot system executed a fully intelligent process including perception, grasping, moving, adjusting, inserting, and screwing. Experimental verification demonstrated millimeter-level precision manipulation in a scene without prior structural modification. The embodied intelligent manipulation method for robots in unstructured environments proposed in this paper can support the development of space intelligent autonomous control technologies for tasks such as on-orbit servicing.

Health assessment of satellite key components is essential for ensuring on-orbit reliability and supporting mission planning. Performance degradation often involves several parameters that change together and show coupled dynamics. A single parameter fails to capture the full evolution of the state, while existing fusion methods rely on expert weighting and cannot represent the dynamic shift in inter-parameter dependence. This study proposed a health assessment method based on coupled deviations in multivariate distributions. We first built a Multivariate Distribution Deviation (MDD) metric and used the Sliced Wasserstein distance to quantify high-dimensional distribution shifts efficiently. The metric captured degradation from two views: marginal variation and coupling-structure change, and avoided the computational burden of the classical Wasserstein distance in high dimensions. We then introduced a Degradation Momentum (DM) metric that accumulated positive increments in distribution-shift rates to describe deviation magnitude and trend strength. MDD and DM jointly formed a two-dimensional state-feature space. Spectral clustering on this space achieved adaptive grading and continuous tracking over the full life cycle. Validation on real data from momentum wheels and gyroscopes showed that the method detected weak early-stage changes, revealed the state-evolution process, and produced stable and interpretable assessments. The approach provides a theoretically sound and practically deployable multivariate strategy for health management of satellite components.

This study aims to balance orbit-keeping accuracy，propellant consumption and computational efficiency for spacecraft station-keeping near Earth-Moon libration points. Traditional nonlinear model predictive control (NMPC) imposes a heavy onboard computational burden because it solves complex nonlinear optimization at every control step. A high-fidelity model is developed based on the circular restricted three-body problem combined with low-thrust orbital dynamics. The research introduces an event-triggered mechanism (ETM) and proposes two event-triggered NMPC (ET-NMPC) algorithms. Instead of fixed-period execution，the controller initiates online receding-horizon optimization only when the real-time position tracking error exceeds a preset threshold. Between triggers，when tracking performance remains satisfactory，two low-computation strategies are applied alternately：control-input freezing and control-input nullification. This design avoids numerous unnecessary online optimizations. Long-term numerical simulations show that the ET-NMPC strategies maintain control precision while greatly lowering computational load. With suitable thresholds，both methods reduce average computation time by over 50% and decrease the average triggering frequency by more than 77% compared with standard NMPC. The approach successfully balances control performance with limited onboard computational resources. The proposed control framework offers a novel ondemand optimization solution for deep-space orbital control under strict resource constraints. It significantly expands the practical applicability of nonlinear model predictive control in complex aerospace dynamical systems.

Lunar environmental uncertainties and measurement errors can degrade guidance accuracy. To address this issue, an optimal covariance control based method was proposed to incorporate stochastic uncertainties into the trajectory optimization process, thereby enhancing robustness against such disturbances. First, the trajectory optimization problem was formulated as a chance-constrained optimal covariance control problem, with fuel optimality as the performance metric. Stochastic differential equations were used to model dynamic uncertainties, and chance constraints were introduced to represent state and thrust constraints. Subsequently, a successive convex optimization algorithm was developed to solve the problem. The dynamics were discretized using a zero-order hold, and a Kalman filter was employed for real-time state estimation. Based on uncertainty propagation in the filtered closed-loop system, a discrete-time stochastic optimization problem was established. Furthermore, the chance constraints were relaxed into deterministic constraints using Gaussian distribution functions. These constraints were then convexified via successive linearization. An approximate solution to the original problem could thus be obtained by iteratively solving the convex subproblem. In numerical simulations, two scenarios are examined to demonstrate the effectiveness of the proposed algorithm, including hopping on a flat lunar surface and hopping into a pit. Under the same constraints, a comparison with deterministic optimization results shows that the closed-loop optimal trajectory obtained by the proposed method has standard deviations of approximately 2m in position and 1m/s in velocity, which are significantly smaller than those of the open-loop method. The fuel consumption for nominal trajectories increases by less than 0.1kg compared with open-loop method, and is less than the linear quadratic regulator (LQR). Therefore, the proposed method can effectively handle the stochastic uncertainties in measurements and dynamics, and significantly improve landing accuracy.

It is important for a lunar lander to possess a large divert capability during the final landing phase, as this can enhance the tolerance for flight deviations in the early phase or improve the obstacle avoidance performance. Therefore, when designing the powered descent trajectory, sufficient final phase divert capability should be reserved at the minimum propellant cost. To this end, a multi-phase trajectory programming (MPTP) method for powered descent with approaching phase divert capability is proposed. First, the entire powered descent trajectory is divided into the main braking phase and the approaching phase. The main braking phase is responsible for dissipating the majority of the initial velocity. The approaching phase is responsible for safely and precisely flying toward the landing site. It is nominally a vertical descent trajectory and possesses equal divert capability in all horizontal directions. Then, a constant-thrust linear tangent guidance (LTG) accounting for the lunar curvature is designed for the main braking phase. For the approaching phase, a variable-thrust lossless convex programming (LCP) guidance considering the constraints of tilt angle and glide-slope angle is developed. Subsequently, to connect the two phases and further optimize the propellant consumption throughout the entire trajectory, a method for determining the phase switching condition is proposed. The originally difficult-to-solve two-parameter optimization problem is decomposed into two more easily solvable subproblems, which are solved iteratively via a bilevel optimization framework. Finally, the divert capability of the proposed method is verified through numerical simulation. The programmed trajectory is basically consistent with the results of the pseudospectral method, with the difference in propellant consumption being only 0.006%. This method is suitable for the rapid iterative design of nominal trajectories for lunar lander powered descent in engineering applications.

For the continuous-thrust pursuit-evasion game scenario of spacecraft in the Earth-Moon space, this paper proposes a rapid saddle point solution method tailored for the restricted three-body environment. First, by introducing a virtual reference object and relative motion theory, a mathematical model for the orbital pursuit-evasion game is established within the framework of the circular restricted three-body problem dynamics. Then, a saddle point initial guess calculation method based on linearization of relative motion is proposed. By performing Taylor expansion of the nonlinear relative motion equations around the reference trajectory, an equivalent linear approximation model of the original problem is constructed, thereby enabling efficient and stable estimation of the saddle point initial guess. Finally, by combining the multiple shooting method, rapid solution of the saddle point for the continuous-thrust pursuit-evasion game in the Earth-Moon space is achieved. Numerical simulations for typical three-body periodic orbits in the Earth-Moon space, such as Distant Retrograde Orbits (DRO), Near-Rectilinear Halo Orbits (NRHO), and L1 Lyapunov orbits, demonstrate that the proposed method can achieve fast and accurate saddle point solutions for pursuit-evasion games across different orbital environments, exhibiting good convergence and generality.

Trajectory tracking control of spacecraft undergoing large-range relative motion is a key problem in on-orbit servicing and related space missions. However, the traditional Clohessy-Wiltshire (C-W) dynamics model based on local linearization suffers from insufficient accuracy in large-range relative motion scenarios and thus fails to meet engineering requirements. To address this issue, a Koopman-based integrated control approach was proposed, in which dynamic modeling, state estimation, and closed-loop control were unified within the global linearization framework of the Koopman operator, aiming to improve control accuracy and performance while maintaining computational efficiency. In this approach, tensor products of state variables were employed as basis functions, and the Koopman operator was efficiently constructed via δ-inner-product operations. On this basis, an online state estimation method was developed by incorporating conjugate unscented transform(CUT), enabling high-accuracy state estimation with only a small number of samples. By freezing the control term, the inherently non-convex optimization problem arising in Koopman-based model predictive control(MPC) was transformed into a convex program, allowing efficient online computation of closed-loop control inputs. Numerical simulations for large-range relative motion trajectory tracking scenarios demonstrate that the proposed method achieves computational efficiency comparable to that of conventional C-W model-based control, while exhibiting clear advantages in control accuracy and performance: fuel consumption is reduced to approximately 35% of that required by the traditional method, and trajectory tracking errors are reduced to about 2% of those obtained using the C-W model. Under near-distance relative motion conditions, the proposed approach naturally reduces into the conventional control strategy, verifying its consistency and generality. The proposed Koopman-based integrated control method provides an effective engineering implementation framework for large-range relative motion trajectory tracking and exhibits promising engineering applicability. 

Tianwen-2 is China's first mission for near-Earth asteroid sampling and main-belt comet exploration. After analyzing the orbital environment and operational requirement, a circular flexible solar wing configuration is adopted, addressing key constraints including operation under low-intensity low-temperature (LILT) conditions, reliable stowage during launch, and long-term tension management. High-efficiency triple-junction GaAs solar cells are developed through bandgap engineering and edge passivation, achieving an average conversion efficiency >34% at 2.5 au. The blanket design uses a modular, mirror-symmetric layout with planarized circuits and lightweight backing to ensure reliable stowage. Thermal simulation and tension compensation are employed to manage internal stresses, while ultra-lightweight support structures and planar stress-relief interconnects maintain ribbon stresses below 80% of the fatigue limit. Simulation and ground testing confirm that the array meets the mission's power needs, with post-deployment verification validating its output performance and operational stability.

With the rapid development of the low-altitude economy, the construction of low-altitude transportation infrastructure has progressed from conceptual exploration to scaled practice. The digital air-route network not only guides the construction of facility and air-internet networks, but also provides the service network with followable routes, making it a priority task in building low-altitude transportation infrastructure. However, the existing methods for constructing digital air-route networks insufficiently consider risk quantification, lack structured topology, and omit essential route attributes. In addition, they have not clarified the required types and geometric accuracies of geographic and constraint elements in low-altitude environments. Therefore, it is necessary to further improve relevant methodologies to better guide the construction and application of digital air-route networks for the low-altitude economy. To address these issues, this study begins with the interaction mechanism between unmanned aerial vehicles (UAVs) and their geographic constraint environments. It identifies the categories of geographic and constraint elements required for digital air-route network construction and specifies the geometric accuracy requirements for geographic elements. The feasibility and adequacy of spaceborne remote sensing techniques for acquiring these elements are analyzed. Based on these findings, a construction method for digital air-route networks is proposed, integrating geographic and constraint information while jointly optimizing topological structure and risk. Field experiments are conducted in Anyang to verify the feasibility of this method, including validation of the spaceborne geographic information base, meteorological constraints, the digital air-route network itself, and the communication and positioning quality along the routes. Results show that spaceborne remote sensing data achieve a DSM vertical accuracy better than 2m, a building white model accuracy of 3.83m, an overall obstacle recognition accuracy of 80.77%, and a land cover classification accuracy of 79.5%. These results collectively meet the meter level geometric and surface-attribute resolution requirements for digital air-route network construction. Compared with manually designed routes, the air-route network generated with this method reduces route length by 7.6%, cruise time by 12.6%, and the proportion of high-risk segments by 7.6%, while increasing the nonlinearity coefficient by 8.2%. Compared with pilot-planned ad-hoc routes, route length decreases by 4.2%, cruise time by 3.4%, and the nonlinearity coefficient improves by 18.5%. Overall, the proposed method effectively improves airspace utilization, reduces flight risk, and enhances flight efficiency, fulfilling the operational requirements for UAVs to fly, fly safely, and fly efficiently in large-scale low-altitude operations. 

The IoT NTN (Internet of Things Non-Terrestrial Network) satellite communication system, based on a transparent forwarding architecture, utilizes Orthogonal Frequency Division Multiple Access (OFDMA) technology. While effective, its performance is significantly sensitive to frequency offset. Currently, engineering practice lacks robust analytical tools to evaluate these effects. To provide a practical frequency offset analysis method for transparent IoT NTN systems, this paper proposes a frequency offset analysis model and offers design recommendations for related performance indicators. Focusing on the limited frequency offset tolerance of the return link, the systems operational limits were determined through rigorous simulation analysis and experimental testing. The study identifies ephemeris errors and clock frequency errors as the primary factors degrading system performance. Results indicate that the return link frequency offset should be maintained below 200Hz. To ensure compliance with this threshold, the following specifications are proposed: the ephemeris error should be kept within 20m, the ground segment clock frequency accuracy should not exceed 3ppb, and the space segment clock frequency accuracy should not exceed 10ppb. Beyond its application to transparent IoT NTN architecture, the research methodology presented here can be extended to the design of frequency offset indicators for broader communication systems, providing a valuable reference for engineering implementation.

This study investigated a generalized beam-element modeling method incorporating complete hinge stiffness and its experimental validation, aiming to address the prediction deviations in dynamics of large articulated truss structures caused by neglecting the actual multi-degree-of-freedom stiffness at hinges in traditional modeling approaches. A modified dynamic formulation was developed within the Timoshenko beam framework by integrating a complete joint stiffness matrix derived from experimental measurements. First, dedicated tests were performed to characterize the six-degree-of-freedom stiffness properties of the structural hinges. Subsequently, a correlated finite-element model was constructed using the acquired data. Finally, experimental modal analysis on a five-bay articulated triangular truss prototype was conducted to validate the model. The modified model demonstrated good agreement with test data, predicting the first two bending frequencies within 10% of measured values. Comparative analysis confirmed its superior accuracy over the conventional ideal-hinge model, underscoring the significant influence of joint stiffness on global structural dynamics. The combined test-simulation modeling methodology, which accounts for hinge stiffness, effectively resolves the systematic model deviations arising from its omission. This approach provides reliable numerical simulation results and theoretical support for the high-precision control and design optimization of large spacecraft truss structures.

Flexible solar arrays and membrane antennas, as typical aerospace structures utilizing tensioned membranes, are highly sensitive to stress variations and prone to wrinkling under compressive loads. To improve the accuracy of analytical stress field modeling, a stress compensation approach based on the principle of superposition is proposed for the free vibration analysis of corner-tensioned membranes.A radial stress distribution model induced by a concentrated force was first employed to construct the initial stress field. Considering the free-boundary characteristics of corner-tensioned membranes, a virtual boundary loading scheme was introduced to compensate the initial stress by applying external loads equal in magnitude and opposite in direction to the normal boundary stress. A vibration model of a square tensioned membrane was developed by incorporating geometric stiffness, mesh generation strategies, and the effect of added air mass. The effectiveness of the proposed method was verified through comparison with finite element simulations and NASA-released experimental data.The calculated first and second principal stresses at the membrane center showed relative errors of 0.93% and 2.15%, respectively, when compared to finite element references. For modal analysis, the theoretical first natural frequency deviated by only 4.6% from experimental results, while the fifth mode exhibited a deviation of 27.7%, confirming the method’s effectiveness in predicting multiple vibration modes with good accuracy.The proposed stress compensation method accurately reconstructs a physically realistic stress field with smooth distribution and natural boundary transitions. It significantly improves the precision of modal predictions and shows strong potential for engineering applications. The method offers a reliable theoretical basis and practical tool for the design and dynamic analysis of flexible aerospace membrane structures.

To address the problem that the continuous expansion of satellite cluster scales and dynamic variations in space target types induce an exponential growth in the dimensionality of the optimal solution space for observation tasks, this study investigated multiangle and omnidirectional sustained observation technologies for space debris, with the aim of improving the observation coverage effectiveness, algorithm convergence stability and multi-scenario adaptability of satellite clusters within the observation time domain.A mathematical characterization model for the space debris observation region was constructed to realize the accurate quantification of the target observed area and blind zone.An improved genetic algorithm was subsequently designed by integrating an adaptive mutation strategy, a roulette-wheel selection operator and an observation task fitness function, thereby achieving the collaborative optimization of initial position deployment for satellite clusters and real-time field-of-view pointing to capture effective surface feature information of space debris throughout the observation time domain.Simulation verification was carried out in two task scenarios configured in the geostationary Earth orbit, namely dispersed debris and concentrated debris.The simulation results show that compared with the dung beetle optimization algorithm, the proposed layout optimization algorithm for space debris group monitoring tasks based on the improved genetic algorithm improves the convergence performance by 10%, achieves a sustained effective observation coverage ratio of more than 82% under scenarios with different satellite scales and target densities, and exhibits high coverage efficiency, strong convergence stability and full-scenario adaptability.This algorithm meets the efficient and sustained observation requirements of sparse to dense space debris groups with various satellite cluster scales, and provides technical support for the task optimization of sustained space debris observation using satellite clusters.

Roving exploration using mobile robots is crucial for extending the breadth and depth of deep space exploration. However, current terrestrial perception methods employed by mobile robots in orbit struggle to effectively identify non-geometric hazards(such as soft sandy areas) under extraterrestrial conditions characterized by rugged and natural terrain, high texture homogeneity, extreme illumination variations, and limited prior knowledge. This limitation consequently compromises the navigational safety of mobile robots.This study designs a soil mechanical properties inference experiment based on multispectral characteristics: spectral characteristics curves and corresponding mechanical parameter databases covering multiple simulated soils are constructed through spectral characteristic measurement experiments and in-situ Bevameter mechanical properties measurement experiments; a hierarchical mapping mechanism of "spectral characteristics-soil type-mechanical properties" is established to qualitatively infer soil mechanical properties; validation is conducted using multispectral image data captured by Zhurong rover. The validation results demonstrate that identifying dominant soil types through spectral features and correlating them with mechanical properties via database allows qualitative inference of surface mechanical parameters, which provides decision support for safe path planning of extraterrestrial robots.