Astrodynamics最新文献

This paper presents a solution to the leaderless consensus of multiple spacecraft on SO(3) under a connected undirected graph. An algorithm is proposed to generate an undirected tree graph from a connected undirected communication topology. A distributed observer is designed to estimate the desired attitude and angular velocity for each spacecraft under the generated tree graph. An adaptive controller with a general connected undirected graph is developed to complete the synchronization task. Cases with zero and nonzero final angular velocities are considered. Theoretical proofs and numerical simulations are presented to demonstrate the effectiveness of the proposed controllers.

The design of complex aerospace systems is a multidisciplinary design optimization (MDO) problem involving the interaction of multiple disciplines. However, because of the necessity of evaluating expensive black-box simulations, the enormous computational cost of solving MDO problems in aerospace systems has also become a problem in practice. To resolve this, metamodel-based design optimization techniques have been applied to MDO. With these methods, system models can be rapidly predicted using approximate metamodels to improve the optimization efficiency. This paper presents an overall survey of metamodel-based MDO for aerospace systems. From the perspective of aerospace system design, this paper introduces the fundamental methodology and technology of metamodel-based MDO, including aerospace system MDO problem formulation, metamodeling techniques, state-of-the-art metamodel-based multidisciplinary optimization strategies, and expensive black-box constraint-handling mechanisms. Moreover, various aerospace system examples are presented to illustrate the application of metamodel-based MDOs to practical engineering. The conclusions derived from this work are summarized in the final section of the paper. The survey results are expected to serve as guide and reference for designers involved in metamodel-based MDO in the field of aerospace engineering.

By considering the spacecraft as an extended, rigid body with a prior known attitude instead of a point mass, the attitude-restricted orbital dynamics can improve the precision of the classical point-mass orbital dynamics in close proximity to an asteroid, because it includes the perturbation caused by the gravitational orbit–attitude coupling of the spacecraft (GOACP). The GOACP is defined as the difference between the gravity acting on a non-spherical, extended body (the real case of a spacecraft) and the gravity acting on a point mass (the approximation of a spacecraft in classical orbital dynamics). In-plane equilibrium points that are within the principal planes of the asteroid have been investigated for the attitude-restricted orbital dynamics in previous studies, including equatorial and in-plane non-equatorial equilibrium points. In this study, out-of-plane equilibrium points outside the principal planes of the asteroid were examined. Out-of-plane equilibrium points cannot exist in the classical point-mass orbital dynamics but do exist in the attitude-restricted orbital dynamics owing to the effects of the GOACP. The previously investigated in-plane equilibrium points and the out-of-plane ones examined in this study provide a complete map of the equilibrium points in close proximity to an asteroid with the GOACP. Equatorial and in-plane non-equatorial equilibrium points have extended the longitude and latitude ranges of the classical equilibrium points without the GOACP, respectively, while the out-of-plane ones examined in the present study extend both the longitude and latitude ranges. Additionally, the invariant manifolds of out-of-plane equilibrium points were calculated, and the results indicated that the attitude of spacecraft significantly affects the invariant manifolds. In practice, these equilibrium points can provide natural hovering positions for operations in proximity to asteroids, and their invariant manifolds can be used for transfers to or from the equilibrium points.

With the increase of space debris, space debris removal has gradually become a major issue to address by worldwide space agencies. Multiple debris removal missions, in which multiple debris objects are removed in a single mission, are an economical approach to purify the space environment. Such missions can be considered typical time-dependent traveling salesman problems (TDTSPs). In this study, an intelligent global optimization algorithm called Timeline Club Optimization (TCO) is proposed to solve multiple debris removal missions of the TDTSP model. TCO adopts the traditional ant colony optimization (ACO) framework and replaces the pheromone matrix of the ACO with a new structure called the Timeline Club. The Timeline Club records which debris object to be removed next at a certain moment from elitist solutions and decides the probability criterion to generate debris sequences in new solutions. Two hypothetical scenarios, the Iridium-33 mission and the GTOC9 mission, are considered in this study. Simulation results show that TCO offers better performance than those of beam search, ant colony optimization, and the genetic algorithm in multiple debris removal missions of the TDTSP model.

The Horyu-VI nano-satellite is an international lunar mission with the purpose of studying the lunar horizon glow (LHG)—a still unclear phenomenon caused by electrostatically charged lunar dust particles. This study analyzes the mission trajectory with the hypothesis that it is launched as a secondary payload of the NASA ARTEMIS-II mission. In particular, the effect of the solar gravity gradient is studied; in fact, depending on the starting relative position of the Moon, the Earth, and the Sun, the solar gradient acts differently on the trajectory—changing it significantly. Therefore, the transfer and lunar capture problem is solved in several cases with the initial Sun–Earth–Moon angle as the key parameter. Furthermore, the inclination with respect to the Moon at capture is constrained to be equatorial. Finally, the problem of stabilization and circularization of the lunar orbit is addressed in a specific case, providing an estimate of the total propellant cost to reach the final orbit around the Moon.

A frozen orbit is beneficial for observation owing to its stationary apsidal line. The traditional gravitational field model of frozen orbits only considers the main zonal harmonic terms J₂ and limited high-order terms, which cannot meet the stringent demands of all missions. In this study, the gravitational field is expanded to J₁₅ terms and the Hamiltonian canonical form described by the Delaunay variables is used. The zonal harmonic coefficients of the Earth are chosen as the sample. Short-periodic terms are eliminated based on the Hori–Lie transformation. An algorithm is developed to solve all equilibrium points of the Hamiltonian function. A stable frozen orbit with an argument of perigee that equals neither 90◦ nor 270◦ is first reported in this paper. The local stability and topology of the equilibrium points are obtained from their eigenvalues. The bifurcations of the equilibrium points are presented by drawing their global long-term evolution of frozen orbits and their orbital periods. The relationship between the terms of the gravitational field and number of frozen points is addressed to explain why only limited frozen orbits are found in the low-order term case. The analytical results can be applied to other Earth-like planets and asteroids.

Countries are increasingly interested in spacecraft surveillance and recognition which play an important role in on-orbit maintenance, space docking, and other applications. Traditional detection methods, including radar, have many restrictions, such as excessive costs and energy supply problems. For many on-orbit servicing spacecraft, image recognition is a simple but relatively accurate method for obtaining sufficient position and direction information to offer services. However, to the best of our knowledge, few practical machine-learning models focusing on the recognition of spacecraft feature components have been reported. In addition, it is difficult to find substantial on-orbit images with which to train or evaluate such a model. In this study, we first created a new dataset containing numerous artificial images of on-orbit spacecraft with labeled components. Our base images were derived from 3D Max and STK software. These images include many types of satellites and satellite postures. Considering real-world illumination conditions and imperfect camera observations, we developed a degradation algorithm that enabled us to produce thousands of artificial images of spacecraft. The feature components of the spacecraft in all images were labeled manually. We discovered that direct utilization of the DeepLab V3+ model leads to poor edge recognition. Poorly defined edges provide imprecise position or direction information and degrade the performance of on-orbit services. Thus, the edge information of the target was taken as a supervisory guide, and was used to develop the proposed Edge Auxiliary Supervision DeepLab Network (EASDN). The main idea of EASDN is to provide a new edge auxiliary loss by calculating the L2 loss between the predicted edge masks and ground-truth edge masks during training. Our extensive experiments demonstrate that our network can perform well both on our benchmark and on real on-orbit spacecraft images from the Internet. Furthermore, the device usage and processing time meet the demands of engineering applications.

Spacecraft collision avoidance procedures have become an essential part of satellite operations. Complex and constantly updated estimates of the collision risk between orbiting objects inform various operators who can then plan risk mitigation measures. Such measures can be aided by the development of suitable machine learning (ML) models that predict, for example, the evolution of the collision risk over time. In October 2019, in an attempt to study this opportunity, the European Space Agency released a large curated dataset containing information about close approach events in the form of conjunction data messages (CDMs), which was collected from 2015 to 2019. This dataset was used in the Spacecraft Collision Avoidance Challenge, which was an ML competition where participants had to build models to predict the final collision risk between orbiting objects. This paper describes the design and results of the competition and discusses the challenges and lessons learned when applying ML methods to this problem domain.

A new era of up-close asteroid exploration has been entered in the 21st century. However, the widely rugged terrain and microgravity field of asteroids still pose significant challenges to the stable landing of spacecraft and may even directly lead to the escape of the explorer. Owing to the substantial energy dissipation arising from the interaction among multiple bodies, the flexible net, which is a typical multibody system, may be capable of overcoming the above problems. In this study, a dynamical model was established to analyze the movement of the flexible net spacecraft (FNS) near and on the asteroid comprehensively. First, we investigated the dynamical environment of the target asteroid by combining the polyhedron method and spherical harmonics parametric surface modeling approach. Thereafter, we constructed the multibody dynamics model of the explorer using the linear Kelvin–Voigt method. Subsequently, we studied the collision process between the FNS and asteroid based on the spring–damper contact dynamics model. The trajectory and speed of the FNS could be derived by solving the system dynamic equations in parallel. Finally, we analyzed the deformation, descent, jumping motion, and surface movement process of the FNS during the movement. Consequently, a promising scheme is provided for asteroid exploration missions in the future.