Astrodynamics最新文献

Owing to the large communication delay in deep space exploration missions, trajectory maneuvers prior to the flyby of small celestial bodies generally need to be scheduled in advance. However, the lack of prior data and the presence of environmental uncertainties in deep space are significant challenges for maneuver scheduling. To solve this problem, in this study, robust maneuver scheduling networks based on proximal policy optimization were proposed. A reward function that considers the terminal state accuracy of the spacecraft after maneuvering and the total velocity impulse cost was designed for the maneuver scheduling networks. An additional constant was added to the variance of the actor network to improve the performance of the generated maneuvering strategy. Compared with the actor-critic algorithm and genetic algorithm, the maneuvering strategy generated by the maneuver scheduling networks demonstrated the best performance in most simulation scenarios and maintained a better balance between the terminal state accuracy and the total velocity impulse cost. The robustness of the maneuver strategy against uncertain perturbations in the environment and uncertain initial state deviations of the spacecraft was validated in several maneuver scenarios in the simulation. In addition, the generated maneuvering strategy exhibited excellent real-time performance. The time cost to make a decision was still better than 0.7 s in the worst case, testing on Raspberry Pi 4B with a memory of 4 GB and a limited CPU frequency of 800 MHz. The robustness against uncertainties and real-time capability of the proposed method revealed its potential onboard application to future deep space exploration missions.

Comet exploration missions represented by the Comet Interceptor mission have attracted our attention to unravel the origin of our solar system. However, it is difficult to know the details of orbital data about long period comets (LPCs) until their approach. Additionally, the amount of fuel consumption by the current intercept approach depends on the intersection points of cometary orbits with the ecliptic plane. To address these challenges, designing low-energy transfer trajectories suitable for the observation of LPCs is necessary. This paper introduces a novel approach by utilizing invariant manifold structures in the Sun-Earth circular restricted three-body problem for comet missions with multiple probes. As candidates for departure orbits, periodic orbits and quasi-periodic orbits are considered. Based on the optimal control theory, low-thrust trajectories to improve mission efficiency for enlarging the reachable domain of multiple probes are designed by leveraging invariant manifolds. The trajectories guided by invariant manifolds and optimal control theory facilitate formation flying, multi-point observations, and explorations of unknown comets by multiple probes.

The performance of space antennas is significantly affected by thermal deformation owing to the harsh thermal environment in space. This results in potential degradation in pointing accuracy and overall functionality. This study focused on the analysis and control of thermal deformation in large-scale two-dimensional planar phased array antennas. Employing the finite element method, we developed a comprehensive thermal and structural model of the antenna. This enabled us to simulate the steady-state temperature field and the associated thermal deformation at various orbital positions. To address this deformation issue, we propose an innovative shape-control approach that utilizes distributed cable actuators. The shape control challenge was reformulated into a layered optimization problem concerning actuator placement and force application. In the outer optimization layer, a discrete particle swarm optimization algorithm was used to determine the optimal locations for the actuators. In the inner optimization layer, quadratic programming was subsequently applied to calculate the optimal control forces for each actuator. We validated the proposed method by numerically simulating a novel large-scale two-dimensional planar phased array antenna. The results demonstrated the effectiveness of our method in mitigating thermal deformation and maintaining the structural integrity and shape accuracy of the antennas.

This paper presents a novel machine learning approach designed to efficiently solve the classical two-body problem. The inherent structure of the two-body problem involves the integration of a system of second-order nonlinear ordinary differential equations. Conventional numerical integration techniques that rely on small computation steps result in a prolonged computational time. Moreover, calculus has limitations in resolving the two-body problem, inevitably converging towards an unresolved Kepler equation of a transcendental nature. To address this issue, we integrate the conventional analytical solution based on true anomaly with a deep neural network representation of the Kepler equation. This results in a highly accurate closed-form solution that is solely dependent on time, which is termed a learning-based solution to the two-body problem. To enhance the precision, a correction module based on Halley iteration is introduced, which substantially improves the final solution in terms of precision and computational cost. Compared to state-of-the-art methods such as the piecewise Padé approximation, Adomian decomposition method, and modified Mikkola’s method, our approach achieves a computational speedup of several thousand to tens of thousands, while maintaining accuracy in large-scale orbit propagation scenarios. Empirical validation under simulated conditions underscores its effectiveness and potential value for long-term orbit determination.

This paper presents new methods for spacecraft relative pose estimation using the Unscented Kalman Filter (UKF), taking into account non-additive process and measurement noises. A twistor model is employed to represent the spacecraft’s relative 6-DOF motion of the chaser with respect to the target, expressed in the chaser body frame. The twistor model utilizes Modified Rodrigues Parameters (MRPs) to represent attitude with a minimal number of parameters, eliminating the need for the normalization constraint that exists in the quaternion-based model. Additionally, it incorporates both relative position and attitude in a single model, addressing kinematic coupling of states and simplifying the estimator design. Despite numerous existing pose estimation algorithms, many rely on the simplification of additive noise assumptions. This work enhances the robustness and improves the convergence of non-additive noise algorithms by deriving two methods to accurately approximate process and measurement noise covariance matrices for systems with non-additive noises. The first method utilizes the Stirling Interpolation Formula (SIF) to obtain equivalent process and measurement noise covariance matrices. The second method employs State Noise Compensation (SNC) to derive the equivalent process noise covariance matrix and uses SIF to compute the equivalent measurement noise covariance matrix. These methods are integrated into the UKF framework for estimating the relative pose of spacecraft in proximity operations, demonstrated through two scenarios: one with a cooperative target using Position Sensing Diodes (PSDs) and another with an uncooperative target using LiDAR for 3-D imaging. The effectiveness of these methods is validated against others in the literature through Monte Carlo simulations, showcasing their faster convergence and robust performance.

The Hayabusa2 extended mission, named Hayabusa2# (SHARP: Small Hazardous Asteroid Reconnaissance Probe), is planned to rendezvous with the fast-rotating asteroid 1998 KY26 in 2031. Hayabusa2# will be the first ever mission to rendezvous with such a rapidly rotating small asteroid, posing significant challenges because of its distinctive dynamical environment. In this paper, we investigate potential target marker (TM) deployment strategies, for both landing and orbiting scenarios, to maximize science acquisition. In particular, we model the surface and orbital environments to identify feasible target market operations and present landing site selection strategies and candidate insertion orbits considering realistic deployment errors. The TM is one of the only two remaining deployable payloads, and therefore, can play a critical role during the extended mission phase. Our results show that surface operations can be extremely challenging whereas orbit operations could help us gain valuable information on the asteroid’s gravity field. Overall, this research contributes to the exploration and characterization of extremely small bodies specifically through the use of artificial objects, in this case the target marker.

In this study, a combined trajectory and time-planning strategy is proposed to reduce the fuel consumption of low-thrust rendezvous missions. First, a transformation method was developed to adjust the independent variable such that results obtained using the shape-based algorithm that employs an inverse polynomial can be used as an initial guess for a pseudospectral method. Second, a planning strategy that combined low-thrust transfer trajectory optimization and boundary condition optimization was designed. This planning strategy was divided into outer and inner layers. The outer plan optimized waiting and transfer times and thus determined boundary conditions. The inner plan optimized the low-thrust transfer trajectory using the pseudospectral method. The inner plan was embedded in the outer plan. Numerical simulations show that the independent variable transformation method is feasible, and the combined use of the shape-based algorithm with the inverse polynomial and pseudospectral method ensures good convergence. The cost of rendezvous missions is significantly decreased using combined trajectory and time optimization.

Traditional landers typically encounter difficulties achieving stable landings because of the weak gravity and complex terrain of small celestial bodies. A multi-node lander with flexible connections can improve the stability of a small celestial body landing. However, this also poses new challenges, particularly for landing guidance in hazardous terrain. To address this problem, an equivalent simplified dynamic model of a multi-node flexible lander is first constructed, and its flat output is determined. Subsequently, a trajectory-planning method combining the flow and vector fields is designed to avoid collision, and the parameters of the vector field are optimized online according to the dynamic and obstacle constraints during the descent process to obtain a more suitable trajectory. Finally, the effectiveness of the proposed trajectory-planning method is verified through comparative simulations of landing and obstacle avoidance from the hover point to the landing area. This study offers new prospects for upcoming small celestial body landing missions in complex terrains.

Fuel-optimal orbit-attitude motion planning for spacecraft close-range rendezvous and synchronization requires solving a two-point boundary value problem with continuous input actuation. This paper presents a geometric approach to the problem, which not only encompasses both translational and rotational dynamics, but also incorporates a novel adaptive multiplier method to enforce actuation constraints during the optimization process. Further, in the case of underactuation, such as small single-thruster spacecraft, the paper proposes a guided technique for the geometric approach to direct the attitude using the optimal translational trajectory. The geometric approach is verified through several case studies, where it is compared against a direct method optimization and a concurrent controller, to demonstrate the computational efficiency as well as resulting optimal trajectories of the approach.

Defense against potentially hazardous asteroids is crucial to human civilization. An asteroid projectile can be redirected to intercept hazardous asteroids by employing gravity assist from the Earth or Moon, thereby effectively altering their trajectory. Such an asteroid defense mode is referred to as “space billiard.” Current investigations regarding mission planning and trajectory design for this mode are either incomplete or contain imperfect perspectives. This article proposes a comprehensive mission planning from spacecraft departure to the impact of a hazardous asteroid with an asteroid projectile. This involves selecting an asteroid projectile, determining the maneuver time, and optimizing the low-thrust trajectory. The particle swarm optimization algorithm for the Lambert problem is introduced to search for the maneuver time, and low-thrust optimization is performed to design the transfer trajectory of the spacecraft. A collision model based on NASA’s DART mission is used to analyze the feasibility of this approach. A classic example where this approach is adopted is for analyzing the hazardous asteroid Apophis. Based on this analysis, an asteroid projectile named 2015 VC2 is selected for simulation. The complete trajectories of the spacecraft and asteroid projectile are simulated, and the feasibility of the scheme is verified. This approach may be a feasible option for defending against hazardous asteroids.