Search Results (54)

The article presents an approach to designing a low-orbit remote Earth sensing spacecraft. The low operational orbit of the satellite is maintained using a corrective electric propulsion system. The comprises an optical imaging system based on the Richey-Cretien telescope design augmented with an additional swivel reflection mirror. The optical system’s layout was optimized to minimize the spacecraft’s midsection area. This reduction in the frontal cross-sectional area decreases the aerodynamic drag forces exerted by the upper atmosphere, thereby reducing the propellant mass required for orbit maintenance. The article presents a model of constraints imposed by the satellite’s power supply system on the operating modes of the electric propulsion system and the orbit correction modes. Finally, a preliminary design of a low-orbit satellite, derived from the proposed approach, is presented. Full article

Deep space exploration missions face technical challenges such as long-distance communication delays and high-precision autonomous positioning. Traditional ground-based telemetry and control as well as inertial navigation schemes struggle to meet mission requirements in the complex environment of deep space. As a vision-based autonomous navigation technology, image-based navigation enables spacecraft to obtain real-time images of the target celestial body surface through a variety of onboard remote sensing devices, and it achieves high-precision positioning using stable terrain features, demonstrating good autonomy and adaptability. Craters, due to their stable geometry and wide distribution, serve as one of the most important terrain features in deep space image-based navigation and have been widely adopted in practical missions. This paper systematically reviews the research progress of deep space image-based navigation technology, with a focus on the main sources of remote sensing data and a comprehensive summary of its typical applications in lunar, Martian, and asteroid exploration missions. Focusing on key technologies in image-based navigation, this paper analyzes core methods such as surface feature detection, including the accurate identification and localization of craters as critical terrain features in deep space exploration. On this basis, the paper further discusses possible future directions of image-based navigation technology in response to key challenges such as the scarcity of remote sensing data, limited computing resources, and environmental noise in deep space, including the intelligent evolution of image navigation systems, enhanced perception robustness in complex environments, hardware evolution of autonomous navigation systems, and cross-mission adaptability and multi-body generalization, providing a reference for subsequent research and engineering practice. Full article

This research proposes a tailored Systems Engineering (SE) design process for the development of Attitude and Orbit Control Systems (AOCS) for small satellites operating in formation. These missions, known as Distributed Spacecraft Missions (DSMs), involve groups of satellites—commonly referred to as satellite constellations—whose primary objective is to maintain controlled relative positioning in three dimensions. In these configurations, each satellite may serve a specific role. For instance, one may act as a navigation reference, while another functions as a communication relay. These roles support synchronized control and ensure mission cohesion. To achieve precise relative positioning, the system must integrate specialized sensors and maintain continuous inter-satellite communication. This capability enables precise navigation across both the space and ground segments, while ensuring high control accuracy. As such, the development of AOCS must be approached as a complex systems challenge, involving the coordinated behavior of multiple autonomous elements working toward a shared mission objective. This study tailors the SE process using the ISO/IEC 15288 standard and incorporates a Model-Based Systems Engineering (MBSE) approach to enhance traceability, consistency, and architectural coherence throughout the system lifecycle. As a result, it proposes a customized SE process for AOCS development that begins in the mission’s conceptual phase and addresses the specific functional and operational demands of formation flying. A conceptual example illustrates the proposed process. It focuses on subsystem coordination, communication needs, and the architecture required to support an AOCS for autonomous satellite formations. Full article

The control accuracy and stability requirements for rotating payloads in remote sensing satellites are becoming increasingly higher. Typically, rotating payloads such as cameras are connected to the satellite body through mechanical bearings. However, clearances in conventional mechanical bearings are inevitable due to assembly tolerances, manufacturing errors, and wear. When clearances exist in the mechanical bearings of cameras, the clearance between the mechanical bearing and the journal can cause impact-induced vibrations. This paper proposes the implementation of magnetic bearings instead of mechanical bearings to connect the payload with the spacecraft body. First, the magnetic bearing is modeled as a rotational joint with clearance in the dynamic system with magnetic constraints. Subsequently, radial and axial magnetic force models are established. Furthermore, a comparative analysis is conducted to investigate the effects of connection approaches, namely traditional mechanical bearing connections and magnetic bearing connections for rotating payloads. Simultaneously, the dynamic responses of rotating payloads under different connections are discussed. The simulation results demonstrate that the camera attitude motion accuracy is improved and the vibration amplitude under disturbance is reduced when using magnetic bearings. Consequently, the magnetic bearing can effectively isolate vibrations and mitigate disturbances, thereby significantly reducing the attitude shake of rotating payloads. Full article

The multi-band atmospheric correction algorithms, now referred to as remote sensing reflectance (R_rs) algorithms, have been implemented on a NASA computing facility for global remote sensing of ocean color and atmospheric aerosol parameters from data acquired with several satellite instruments, including the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi spacecraft platform. These algorithms are based on the 2-band version of the SeaWiFS (Sea-Viewing Wide Field-of-View Sensor) algorithm. The bands centered near 0.75 and 0.865 μm are used for atmospheric corrections. In order to obtain high-quality R_rs values over Case 1 waters (deep clear ocean waters), strict masking criteria are implemented inside these algorithms to mask out thin clouds and very turbid water pixels. As a result, R_rs values are often not retrieved over bright Case 2 waters. Through our analysis of VIIRS data, we have found that spatial features of bright Case 2 waters are observed in VIIRS visible band images contaminated by thin cirrus clouds. In this article, we describe methods of combining cirrus and aerosol corrections to improve spatial coverage in R_rs retrievals over Case 2 waters. One method is to remove cirrus cloud effects using our previously developed operational VIIRS cirrus reflectance algorithm and then to perform atmospheric corrections with our updated version of the spectrum-matching algorithm, which uses shortwave IR (SWIR) bands above 1 μm for retrieving atmospheric aerosol parameters and extrapolates the aerosol parameters to the visible region to retrieve water-leaving reflectances of VIIRS visible bands. Another method is to remove the cirrus effect first and then make empirical atmospheric and sun glint corrections for water-leaving reflectance retrievals. The two methods produce comparable retrieved results, but the second method is about 20 times faster than the spectrum-matching method. We compare our retrieved results with those obtained from the NASA VIIRS R_rs algorithm. We will show that the assumption of zero water-leaving reflectance for the VIIRS band centered at 0.75 μm (M6) over Case 2 waters with the NASA R_rs algorithm can sometimes result in slight underestimates of water-leaving reflectances of visible bands over Case 2 waters, where the M6 band water-leaving reflectances are actually not equal to zero. We will also show conclusively that the assumption of thin cirrus clouds as ‘white’ aerosols during atmospheric correction processes results in overestimates of aerosol optical thicknesses and underestimates of aerosol Ångström coefficients. Full article

Accurate thermospheric mass density (TMD) prediction is critical for applications in solar-terrestrial physics, spacecraft safety, and remote sensing systems. While existing deep learning (DL)-based TMD models are predominantly data-driven, their performance remains constrained by observational data limitations. This study proposes ResNet-MSIS, a novel hybrid framework that integrates prior knowledge from the empirical NRLMSIS-2.1 model into a residual network (ResNet) architecture. The incorporation of NRLMSIS-2.1 enhanced the performance of ResNet-MSIS, yielding a lower root mean squared error (RMSE) of 0.2657 × ${10}^{-12}$ kg/m³ in TMD prediction compared with 0.2750 × ${10}^{-12}$ kg/m³ from ResNet, along with faster convergence during training and better generalization on Gravity Recovery and Climate Experiment (GRACE-A) data, which was trained and validated on the CHAllenging Minisatellite Payload (CHAMP) TMD data (2000–2009, altitude of 305–505 km, avg. 376 km) under quiet geomagnetic conditions (Kp ≤ 3). The DL model was subsequently tested on the remaining CHAMP-derived TMD observations, and the results demonstrated that ResNet-MSIS outperformed both ResNet and NRLMSIS-2.1 on the test dataset. The model’s robustness was further demonstrated on GRACE-A data (2002–2009, altitude of 450–540 km, avg. 482 km) under magnetically quiet conditions, with the RMSE decreasing from 0.3352 × ${10}^{-12}$ kg/m³ to 0.2959 × ${10}^{-12}$ kg/m³, indicating improved high-altitude prediction accuracy. Additionally, ResNet-MSIS effectively captured the horizontal TMD variations, including equatorial mass density anomaly (EMA) and midnight density maximum (MDM) structures, confirming its ability to learn complex spatiotemporal patterns. This work underscores the value of merging data-driven methods with domain-specific prior knowledge, offering a promising pathway for advancing TMD modeling in space weather and atmospheric research. Full article

A star tracker is widely used as a high-precision attitude measurement device for spacecraft. It calculates attitude by extracting the magnitude and the position of presumed detected stars by a CCD/CMOS sensor and matching them with stars in the star catalog. The traditional star identification methods typically require the selection of specific anchor stars, which may cause insufficient identification accuracy as the number of stars used in the rough search is limited. In this paper, we propose a star identification method based on spatial projection, which starts with preprocessing. Then, a method for online expansion and reconstruction of the star catalog is proposed, which provides more stored star data. After the rough recognition and coordinate system transformation, the final identification is realized in the polar coordinate system. All the star points in the star image are identified, and the attitude information is obtained at the same time. The performance of the identification method is verified by real night sky experiments. Stray light experiments are also carried out to prove good noise immunity capabilities. Compared with the traditional subgraph isomorphism method, the proposed method makes it easier to adjust the number of recognizable stars in the field of view and better recognition of specific areas. The method is of great significance for future tasks such as attitude measurement, celestial navigation, remote sensing measurement, and space target observation and tracking. Full article

NASA’s Juno mission, involving a pioneering spacecraft the size of a basketball court, has been instrumental in observing Jupiter’s atmosphere and surface from orbit since it reached the intended orbit. Over its first decade of operation, Juno has provided unprecedented insights into the solar system’s origins through advanced remote sensing and technological innovations. This study focuses on change detection in terms of Juno’s trajectory, leveraging cutting-edge data computing techniques to analyze its orbital dynamics. Utilizing 3D position and velocity time series data from NASA, spanning 11 years and 5 months (August 2011 to January 2023), with 5.5 million samples at 1 min accuracy, we examine the spacecraft’s trajectory modifications. The instantaneous average acceleration, jerk, and snap are computed as approximations of the first, second, and third derivatives of velocity, respectively. The Hilbert transform is employed to visualize the spectral properties of Juno’s non-stationary 3D movement, enabling the detection of extreme events caused by varying forces. Two unsupervised machine learning algorithms, DBSCAN and OPTICS, are applied to cluster the sampling events in two 3D state spaces: (velocity, acceleration, jerk) and (acceleration, jerk, snap). Our results demonstrate that the OPTICS algorithm outperformed DBSCAN in terms of the outlier detection accuracy across all three operational phases (OP1, OP2, and OP3), achieving accuracies of 99.3%, 99.1%, and 98.9%, respectively. In contrast, DBSCAN yielded accuracies of 98.8%, 98.2%, and 97.4%. These findings highlight OPTICS as a more effective method for identifying outliers in elliptical orbit data, albeit with higher computational resource requirements and longer processing times. This study underscores the significance of advanced machine learning techniques in enhancing our understanding of complex orbital dynamics and their implications for planetary exploration. Full article

The time period around the Noachian–Hesperian boundary, 3.7 billionyears ago, was an epoch when great geodynamical and environmental changes occurred on Mars. Currently available remote sensing data are crucial for understanding the Martian heat loss pattern and its global thermal state in this transitional period. We here derive surface heat flows in specific locations based on the estimations of the depth of five large thrust faults in order to constrain both surface and mantle heat flows. Then, we use heat-producing element (HPE) abundances mapped from orbital measurements by the Gamma-Ray Spectrometer (GRS) onboard the Mars Odyssey 2001 spacecraft and geographical crustal thickness variations to produce a global model for the surface heat flow. The heat loss contribution of large mantle plumes beneath the Tharsis and Elysium magmatic provinces is also considered in our final model. We thus obtain a map of the heat flow variation across the Martian surface at the Noachian–Hesperian boundary. Our model also predicts an average heat flow between 32 and 50 mW ${\mathrm{m}}^{-2}$, which implies that the heat loss of Mars at that time was lower than the total radioactive heat production of the planet, which has profound implications for the thermal history of Mars. Full article

Ariel (Atmospheric Remote-sensing Infrared Exoplanet Large-survey) is the ESA Cosmic Vision M4 mission, selected in March 2018 and officially adopted in November 2020, whose launch is scheduled by 2029. It aims at characterizing the atmospheres of hundreds of exoplanets orbiting nearby stars by low-resolution primary and secondary transit spectroscopy. The Ariel spacecraft’s operational orbit is baselined as a large-amplitude, eclipse-free halo orbit around the second Lagrangian (L2) point, a virtual point located at about 1.5 million km from the Earth in the anti-Sun direction, as it offers the possibility of long uninterrupted observations in a fairly stable radiative and thermo-mechanical environment. A direct escape injection with a single passage through the Van Allen radiation belts is foreseen. During both the injection trajectory and the final orbit around L2, Ariel will be immersed in and interact with Sun radiation and the plasma environment. These interactions usually result in the accumulation of net electrostatic charge on the external surfaces of the spacecraft, leading to a potentially hazardous configuration for the nominal operation and survivability of the Ariel platform and its payload, as it may induce harmful electrostatic discharges (ESDs). This work presents the latest results collected from surface charging analyses conducted using the SPIS tool of the European SPINE community along the GEO insertion orbit segment and operational orbit. Full article

The problem of the effective control of a small spacecraft is very relevant for solving a number of target tasks. Such tasks include, for example, remote sensing of the Earth or the implementation of gravity-sensitive processes. Therefore, it is necessary to develop new technologies for controlling small spacecraft. These technologies must take into account a number of disturbing factors that have not been taken into account previously. Temperature shock is one such factor for small spacecraft with solar panels. Therefore, the goal of the work is to create a new technology for controlling a small spacecraft based on a mathematical model of the stressed/deformed state of a solar panel during a temperature shock. The main methods for solving the problem are mathematical methods for solving initial/boundary value problems, in particular, the initial/boundary value problem of the third kind. As a result, an approximate solution for the deformation of a solar panel during a temperature shock was obtained. This solution is more general than those obtained previously. In particular, it satisfies the symmetrical condition of the solar panel. This could not be achieved by the previous solutions. We also observe an improvement (as compared to the previous solutions) in the fulfillment of the boundary conditions for the whole duration of the temperature shock. Based on this, a new technology for controlling a small spacecraft was created and its effectiveness was demonstrated. Application of the developed technology will improve the performance of the target tasks such as remote sensing of the Earth or the implementation of gravity-sensitive processes. Full article

A solar sail is a propellantless propulsion system that allows a spacecraft to use solar radiation pressure as a propulsive source for planetary and deep space missions that would be difficult, or even unfeasible, to accomplish with more conventional thrusters, either chemical or electric. A challenging application for these fascinating propulsion systems is a heliocentric mission that requires a displaced non-Keplerian orbit (DNKO), that is, a solar sail-induced closed trajectory in which the orbital plane does not contain the Sun’s center of mass. In fact, thanks to the pioneering work of McInnes, it is known that a solar sail is able to reach and maintain a family of heliocentric DNKOs of given characteristics. The aim of this paper is to analyze the properties of Mars-synchronous circular DNKOs, which have an orbital period matching that of the planet for remote sensing applications. In fact, those specific displaced orbits allow a scientific probe to continuously observe the high-latitude regions of Mars from a quasi-stationary position relative to the planet. In this context, this paper also analyzes the optimal (i.e., the minimum-time) heliocentric transfer trajectory from the Earth to circular DNKOs in two special mission scenarios taken as a reference. Full article

As a natural satellite of the Earth, the moon is a prime target for planetary remote sensing exploration. However, lunar polarization studies are not popular in the planetary science community. Polarimetry of the lunar surface had not been carried out from a spacecraft until the Korean lunar exploration program was initiated. In previous polarization observations of the moon, images of different polarization states were obtained by a rotating linear polarizer. This method is not well suited for future polarization observations from space-based spacecraft. To this end, we present a new kind of polarized observation of the moon using a division of a focal-plane polarization camera and propose a pipeline on the processing method of the polarization observation of the moon. We obtain a map of the degree of white-light polarization on the nearside of the moon through polarization observation, data processing, and correction. The observation and data processing methods presented in this study have the potential to serve as a reference for analyzing polarization observation data from future orbiting spacecraft. These are expected to lead to new discoveries in the fields of astronomy and planetary science. Full article

The field of planetary mapping and cartography builds almost exclusively on remote-sensing data and can be defined by three distinct concepts: systematic imaging as performed through spacecraft surveying, reference mapping as performed through the compilation of reference maps, i.e., regional to global image and topographic maps, and thematic mapping, which aims at abstracting and contextualizing spatial information to generate complex thematic maps, such as geologic or geomorphologic maps. While thematic mapping represents the highest form of abstraction of information that is provided through systematic mapping, thematic mapping also provides scientific reasoning in support of systematic mapping and exploration through spatially contextualized knowledge. For the development of knowledge, it is paramount to manage and exploit the value of thematic maps as research products, and to design a reliable and transparent development process from the beginning of the mapping phase as there is almost no validation for thematic maps. A key element in accomplishing these objectives is well-designed structures and metadata which are maintained within spatial data infrastructures (SDI) and shared as a coordinated process in research data management through data models. In this contribution, we focus on the need to transfer planetary thematic maps into findable, accessible, interoperable, reusable (FAIR), as well as transparent research data assets to facilitate improved knowledge extraction and also to compensate for limitations caused by the lack of conventional validation options. We review the current status of planetary thematic mapping, and we discuss the principles and roles of mappers and publishers in the process of creating and stewarding digital planetary maps and associated data products. We then present and discuss a set of recommendations that are closely tied to the FAIR concepts in research data management to accomplish such tasks. Full article

Planetary radar observations have provided invaluable information on the solar system through both ground-based and space-based observations. In this overview article, we summarize how radar observations have contributed in planetary science, how the radar technology as a remote-sensing method for planetary exploration and the methods to interpret the radar data have advanced in the eight decades of increasing use, where the field stands in the early 2020s, and what are the future prospects of the ground-based facilities conducting planetary radar observations and the planned spacecraft missions equipped with radar instruments. The focus of the paper is on radar as a remote-sensing technique using radar instruments in spacecraft orbiting planetary objects and in Earth-based radio telescopes, whereas ground-penetrating radar systems on landers are mentioned only briefly. The key scientific developments are focused on the search for water ice in the subsurface of the Moon, which could be an invaluable in situ resource for crewed missions, dynamical and physical characterization of near-Earth asteroids, which is also crucial for effective planetary defense, and a better understanding of planetary geology. Full article