Search Results (35)

The Moon has become the focus of renewed interest for numerous space agencies and private companies worldwide. In the coming years, various scientific and commercial missions are planned, with a particular emphasis on exploring the South Pole. These missions include orbiters, landers, as well as both static and mobile rovers. For all these operations, continuous and accurate position knowledge is essential. This paper evaluates the performance of a navigation system designed for a lunar rover using the future satellite navigation infrastructure. It highlights the critical role of integrating multiple information sources, including a Digital Elevation Model (DEM) of the lunar surface and a high-precision Inertial Measurement Unit (IMU). The results demonstrate that a comprehensive suite of instruments enables highly accurate and reliable navigation for a mobile rover. While standalone satellite navigation, due to the reduced number of available sources, offers navigation accuracy of the orders of tens of meters, the addition of the DEM lowers the error at 5 m level; the IMU further improve by roughly 40% the performance on horizontal positioning. Full article

The permanently shadowed regions of the lunar South Pole have become a key target for international lunar exploration due to their unique scientific value and engineering challenges. In order to effectively screen suitable landing zones near the lunar South Pole, this research proposes a comprehensive evaluation method based on a self-organizing map (SOM). Using multi-source remote sensing data, the method classifies and analyzes candidate landing zones by combining scientific purposes (such as hydrogen abundance, iron oxide abundance, gravity anomalies, water ice distance analysis, and geological features) and engineering constraints (such as Sun visibility, Earth visibility, slope, and roughness). Through automatic clustering, the SOM model finds the important regions. Subsequently, it integrates with a supervised learning model, a random forest, to determine the feature importance weights in more detail. The results from the research indicate the following: the areas suitable for landing account for 9.05%, 5.95%, and 5.08% in the engineering, scientific, and synthesized perspectives, respectively. In the weighting analysis of the comprehensive data, the weights of Earth visibility, hydrogen abundance, kilometer-scale roughness, and slope data all account for more than 10%, and these are thought to be the four most important factors in the automated site selection process. Furthermore, the kilometer-scale roughness data are more important in the comprehensive weighting, which is in line with the finding that the kilometer-scale roughness data represent both surface roughness from an engineering perspective and bedrock geology from a scientific one. In this study, a local examination of typical impact craters is performed, and it is confirmed that all 10 possible landing sites suggested by earlier authors are within the appropriate landing range. The findings demonstrate that the SOM-model-based analysis approach can successfully assess lunar South Pole landing areas while taking multiple constraints into account, uncovering spatial distribution features of the region, and offering a rationale for choosing desired landing locations. Full article

The lunar south pole has gained significant attention due to its unique scientific value and potential for supporting future human exploration. Its potential water ice reservoirs and favourable conditions for long-term habitation make it a strategic target for upcoming space missions. This has led to a continuous increase in missions towards the Moon thanks mainly to the boost provided by NASA’s Artemis programme. This study focuses on designing a satellite constellation to provide communication coverage for the lunar south pole. Among the various cislunar orbits analysed, the halo orbit families near Earth–Moon Lagrangian points L1 and L2 emerged as the most suitable ones for ensuring continuous communication while minimising the number of satellites required. These orbits, first described by Farquhar in 1966, allow spacecraft to maintain constant communication with Earth due to their unique geometric properties. The candidate orbits were initially implemented in MATLAB using the Circular Restricted Three-Body Problem (CR3BP) to analyse their main features such as stability, periodicity, and coverage time percentage. In order to develop a more detailed and realistic scenario, the obtained initial conditions were refined using a full ephemeris model, incorporating a ground station located near the Connecting Ridge Extension to evaluate communication performance depending on the minimum elevation angle of the antenna. Different multi-body constellations were propagated; however, the constellation consisting of three satellites around L2 and a single satellite around L1 turned out to be the one that best matches the coverage requirements. Full article

The Chinese Chang’E-7 (CE-7) mission is planned to land in the lunar south polar region, and then deploy a mini-flying probe to fly into the cold trap to detect the water ice. The selection of a landing site is crucial for ensuring both a safe landing and the successful achievement of its scientific objectives. This study presents a method for landing site selection in the challenging environment of the lunar south pole, utilizing multi-source remote sensing data. First, the likelihood of water ice in all cold traps within 85°S is assessed and prioritized using neutron spectrometer and hyperspectral data, with the most promising cold traps selected for sampling by CE-7’s mini-flying probe. Slope and illumination data are then used to screen feasible landing sites in the south polar region. Feasible landing sites near cold traps are aggregated into larger landing regions. Finally, high-resolution illumination maps, along with optical and radar images, are employed to refine the selection and identify the optimal landing sites. Six potential landing sites around the de Gerlache crater, an unnamed cold trap at (167.10°E, 88.71°S), Faustini crater, and Shackleton crater are proposed. It would be beneficial for CE-7 to prioritize mapping these sites post-launch using its high-resolution optical camera and radar for further detailed landing site investigation and evaluation. Full article

This research addresses minimum-fuel pinpoint lunar landing at the South Pole, focusing on trajectory design and near-optimal guidance aimed at driving a spacecraft from a circular low lunar orbit (LLO) to an instantaneous hovering state above the lunar surface. Orbit dynamics is propagated in a high-fidelity ephemeris-based framework, which employs spherical coordinates as the state variables and includes several harmonics of the selenopotential, as well as third-body gravitational perturbations due to the Earth and Sun. Minimum-fuel two-impulse descent transfers are identified using Lambert problem solutions as initial guesses, followed by refinement in the high-fidelity model, for a range of initial LLO inclinations. Then, a feedback Lambert-based impulsive guidance algorithm is designed and tested through a Monte Carlo campaign to assess the effectiveness under non-nominal conditions related to injection and actuation errors. Because the last braking maneuver is relatively large, a finite-thrust, locally flat, near-optimal guidance is introduced and applied. Simplified dynamics is assumed for the purpose of defining a minimum-time optimal control problem along the last thrust arc. This admits a closed-form solution, which is iteratively used until the desired instantaneous hovering condition is reached. The numerical results in non-nominal flight conditions testify to the effectiveness of the guidance approach at hand in terms of propellant consumption and precision at landing. Full article

The Chang’e-6 (CE-6) landing area on the far side of the Moon is located in the southern part of the Apollo basin within the South Pole–Aitken (SPA) basin. The statistical analysis of impact craters in this region is crucial for ensuring a safe landing and supporting geological research. Aiming at existing impact crater identification problems such as complex background, low identification accuracy, and high computational costs, an efficient impact crater automatic detection model named YOLOv8-LCNET (YOLOv8-Lunar Crater Net) based on the YOLOv8 network is proposed. The model first incorporated a Partial Self-Attention (PSA) mechanism at the end of the Backbone, allowing the model to enhance global perception and reduce missed detections with a low computational cost. Then, a Gather-and-Distribute mechanism (GD) was integrated into the Neck, enabling the model to fully fuse multi-level feature information and capture global information, enhancing the model’s ability to detect impact craters of various sizes. The experimental results showed that the YOLOv8-LCNET model performs well in the impact crater detection task, achieving 87.7% Precision, 84.3% Recall, and 92% AP, which were 24.7%, 32.7%, and 37.3% higher than the original YOLOv8 model. The improved YOLOv8 model was then used for automatic crater detection in the CE-6 landing area (246 km × 135 km, with a DOM resolution of 3 m/pixel), resulting in a total of 770,671 craters, ranging from 13 m to 19,882 m in diameter. The analysis of this impact crater catalogue has provided critical support for landing site selection and characterization of the CE-6 mission and lays the foundation for future lunar geological studies. Full article

The Apollo basin is a well-preserved double-ringed impact basin located on the northeastern edge of the South Pole–Aitken (SPA) basin. The Apollo basin has been flooded and filled with large volumes of mare lavas, indicating an active volcanism history. Based on orbital data, we reveal that the Apollo basin exhibits an overall asymmetric configuration in the distribution of mare basalts as well as its topography, chemical compositions, and crustal thickness. The Apollo basin is an excellent example for assessing the influences of the above factors on mare basalts petrogenesis and evaluating mare basalt genesis models. It was found that the generation of mare basalt magmas and their emplacement in the Apollo basin seems to be strongly related to local thin crust (<30 km), but the formation of basaltic magmas should be independent of the decompression melting because the mare units (3.34–1.79 Ga) are much younger than the pre-Nectarian Apollo basin. The mare basalts filled in the Apollo basin exhibits a large variation of TiO₂ abundances, indicating the heterogeneity of mantle sources, which is possible due to the lunar mantle overturn after the LMO solidification or the impact-induced mantle convection and migration. However, the prolonged mare volcanic history of the Apollo basin is not well explained, especially considering the low Th abundance (<2 ppm) of this region. In addition, the central mare erupted earlier than other mare units within the Apollo basin, which seems to contradict the predictions of the postbasin loading-induced stresses model. Laboratory investigations of the Chang’E-6 mare basalt samples could possibly answer the above questions and provide new insight into the mare volcanic history of the lunar farside and the connections between mare volcanism and impact basin formation/evolution. Full article

Particle radiation on the Moon is influenced by a combination of galactic cosmic rays, high-energy solar particles, and secondary particles interacting on the lunar surface. When China’s Chang’e-7 lander lands at the Moon’s South Pole, it will encounter this complex radiation environment. Therefore, a payload detection technology was developed to comprehensively measure the energy spectrum, direction, and radiation effects of medium- and high-energy charged particles on the lunar surface. During the ground development phase, the payload performance was tested against the design specifications. The verification results indicate that the energy measurement ranges are 30 keV to 300 MeV for protons, 30 keV to 12 MeV for electrons, and 8 to 400 MeV/n for heavy ions. The energy resolution is 10.81% for 200 keV electrons of the system facing the lunar surface; the dose rate measurement sensitivity is 7.48 µrad(Si)/h; and the LET spectrum measurement range extends from 0.001 to 37.014 MeV/(mg/cm²). These comprehensive measurements are instrumental in establishing a lunar surface particle radiation model, enhancing the understanding of the lunar radiation environment, and supporting human lunar activities. Full article

The Chang’E-6 (CE-6) mission successfully returned 1935.3 g of lunar soil samples from the Apollo basin within the South Pole–Aitken basin. One of its scientific objectives is to investigate the subsurface structure and regolith thickness at the landing site. Using remote sensing datasets, we estimated the regolith and basalt thicknesses at the landing site by employing the crater morphology method and crater excavation technique. A total of 53 concentric craters and 108 fresh craters with varying excavation depths were identified. Our results indicate that the regolith thickness at the CE-6 landing site ranges from 1.1 to 7.0 m, with an average thickness of 3.5 m. Beneath the regolith, the basalt layer consists of high-Ti basalt overlaying low-Ti basalt, with a total thickness of approximately 64 to 82 m, of which the high-Ti basalt layer accounts for about 22 to 30 m. Based on the local geological history, we proposed a stratigraphy at the CE-6 landing site. These findings provide valuable geological context for interpreting the Lunar Penetrating Radar data and analyzing the returned samples. Full article

The physical properties of lunar regolith are crucial for exploration planning, hazard assessment, and characterizing scientific targets at global and polar scales. The dielectric constant, a key property, offers insights into lunar material distribution within the regolith and serves as a proxy for identifying volatile-rich regoliths. Miniature radio frequency (Mini-RF) on the Lunar Reconnaissance Orbiter (LRO) provides a potential tool for mapping the lunar regolith’s physical nature and assessing the lunar volatile repository. This study presents global and polar S-band Mini-RF dielectric signatures of the Moon, obtained through a novel deep learning inversion model applied to Mini-RF mosaics. We achieved good agreement between training and testing of the model, yielding a coefficient of determination (R² value) of 0.97 and a mean squared error of 0.27 for the dielectric constant. Significant variability in the dielectric constant is observed globally, with high-Ti mare basalts exhibiting lower values than low-Ti highland materials. However, discernibility between the South Pole–Aitken (SPA) basin and highlands is not evident. Despite similar dielectric constants on average, notable spatial variations exist within the south and north polar regions, influenced by crater ejecta, permanently shadowed regions, and crater floors. These dielectric differences are attributed to extensive mantling of lunar materials, impact cratering processes, and ilmenite content. Using the east- and west-looking polar mosaics, we estimated an uncertainty (standard deviation) of 1.01 in the real part and 0.03 in the imaginary part of the dielectric constant due to look direction. Additionally, modeling highlights radar backscatter sensitivity to incidence angle and dielectric constant at the Mini-RF wavelength. The dielectric constant maps provide a new and unique perspective of lunar terrains that could play an important role in characterizing lunar resources in future targeted human and robotic exploration of the Moon. Full article

In recent years, interest in the Moon has grown exponentially, thanks mainly to space programs with strong international cooperation, such as the NASA Artemis program. Several scientific committees have identified the lunar south pole as the region of greatest interest for building a lasting and sustainable human settlement. However, the knowledge we have of this area is still limited. This work aims to provide a general overview of the main physical and morphological features of the lunar south pole and to propose a first iteration of spectroscopic observations within the visible range from the Asiago Astrophysical Observatory, giving a new and different perspective. The objective is to verify the feasibility of an Earth-based spectroscopic survey to detect water and the abundances of other volatiles and elements. Full article

High-resolution and high-accuracy mapping products of the Lunar South Pole (LSP) will play a vital role in future lunar exploration missions. Existing lunar global mapping products cannot meet the needs of engineering tasks, such as landing site selection and rover trajectory planning, at the LSP. The Lunar Reconnaissance Orbiter (LRO)’s narrow-angle camera (NAC) can acquire submeter images and has returned a large amount of data covering the LSP. In this study, we combine stereo-photogrammetry and photoclinometry to generate high-resolution digital orthophoto maps (DOMs) and digital elevation models (DEMs) using LRO NAC images for a candidate landing site at the LSP. The special illumination and landscape characteristics of the LSP make the derivation of high-accuracy mapping products from orbiter images extremely difficult. We proposed an easy-to-implement shadow recognition and contrast stretching method based on the histograms of the LRO NAC images, which is beneficial for photogrammetric and photoclinometry processing. In order to automatically generate tie points, we designed an image matching method considering LRO NAC images’ features of long strips and large data volumes. The terrain and smoothness constraints were introduced into the cost function of photoclinometry adjustment, excluding pixels in shadow areas. We used 61 LRO NAC images to generate mapping products covering an area of 400 km². The spatial resolution of the generated DOMs was 1 m/pixel, and the grid spacing of the derived DEMs was 1 m (close to the spatial resolution of the original images). The generated DOMs achieved a relative accuracy of better than 1 pixel. The geometric accuracy of the DEM derived from photoclinometry was consistent with the lunar orbiter laser altimeter (LOLA) DEM with a root mean square error of 0.97 m and an average error of 0.17 m. Full article

Chang’e-6 (CE-6) is the first sample-return mission from the lunar farside and will be launched in May of 2024. The landing area is in the south of the Apollo basin inside the South Pole Aitken basin. Statistics and analyses of impact craters in the landing area are essential to support safe landing and geologic studies. In particular, the crater size–frequency distribution information of the landing area is critical to understanding the provenance of the CE-6 lunar samples to be returned and can be used to verify and refine the lunar chronology model by combining with the radioisotope ages of the relevant samples. In this research, a digital orthophoto map (DOM) mosaic with resolution of 3 m/pixel of the CE-6 landing area was generated from the 743 Narrow Angle Camera of the Lunar Reconnaissance Orbiter Camera. Based on the DOM, craters were extracted by an automated method and checked manually. A total of 770,731 craters were extracted in the whole area of 246 km × 135 km, 511,484 craters of which were within the mare area. Systematic analyses of the crater distribution, completeness, spatial density, and depth-to-diameter ratio were conducted. Geologic model age estimation was carried out in the mare area that was divided into three geologic units according to the TiO₂ abundance. The result showed that the east part of the mare had the oldest model age of $\mu {3.27}_{-0.045}^{+0.036}$ Ga, and the middle part of the mare had the youngest model age of $\mu {2.49}_{-0.073}^{+0.072}$ Ga. The crater catalogue and the surface model age analysis results were used to support topographic and geologic analyses of the pre-selected landing area of the CE-6 mission before the launch and will contribute to further scientific researches after the lunar samples are returned to Earth. Full article

Excluding rough areas with surface rocks and craters is critical for the safety of landing missions, such as China’s Chang’e-7 mission, in the permanently shadowed region (PSR) of the lunar south pole. Binned digital elevation model (DEM) data can describe the undulating surface, but the DEM data can hardly detect surface rocks because of median-averaging. High-resolution images from a synthetic aperture radar (SAR) can be used to map discrete rocks and small craters according to their strong backscattering. This study utilizes the You Only Look Once version 7 (YOLOv7) tool to detect varying-sized craters in SAR images. It also employs the Markov random field (MRF) algorithm to identify surface rocks, which are usually difficult to detect in DEM data. The results are validated by optical images and DEM data in non-PSR. With the assistance of the DEM data, regions with slopes larger than 10° are excluded. YOLOv7 and MRF are applied to detect craters and rocky surfaces and exclude regions with steep slopes in the PSRs of craters Shoemaker, Slater, and Shackleton, respectively. This study proves SAR images are feasible in the selection of landing sites in the PSRs for future missions. Full article

The International Lunar Research Station, to be established around 2030, will equip lunar rovers with robotic arms as constructors. Construction requires lunar soil and lunar rovers, for which rovers must go toward different waypoints without encountering obstacles in a limited time due to the short day, especially near the south pole. Traditional planning methods, such as uploading instructions from the ground, can hardly handle many rovers moving on the moon simultaneously with high efficiency. Therefore, we propose a new collaborative path-planning method based on deep reinforcement learning, where the heuristics are demonstrated by both the target and the obstacles in the artificial potential field. Environments have been randomly generated where small and large obstacles and different waypoints are created to collect resources, train the deep reinforcement learning agent to propose actions, and lead the rovers to move without obstacles, finish rovers’ tasks, and reach different targets. The artificial potential field created by obstacles and other rovers in every step affects the action choice of the rover. Information from the artificial potential field would be transformed into rewards in deep reinforcement learning that helps keep distance and safety. Experiments demonstrate that our method can guide rovers moving more safely without turning into nearby large obstacles or collision with other rovers as well as consuming less energy compared with the multi-agent A-Star path-planning algorithm with improved obstacle avoidance method. Full article