Astrodynamics最新文献

This study involved simulations and experiments aimed at assessing the efficacy of a tether net in encapsulating space debris. The tether net was modeled as a spring–mass–damper system considering the influence of aerodynamic and gravitational forces and the occurrence of debris collisions. To examine the influence of collision position and size disparity between the debris and the net on debris capture status, the entanglement nodes of the net were identified. Experiments were conducted to evaluate the wrapping capabilities of the tether net, focusing specifically on debris capture. Subsequently, the results were compared with those of the numerical simulation. In the experiments, radio frequency identification was used to identify the entanglement points of the tether net. Previous studies have indicated that the ideal collision point for capturing debris using a tether net with the debris intended to be captured is located at the center of the net. However, the experimental results of this study revealed that a collision position that is slightly shifted from the center of the tether net is more advantageous for capturing debris in terms of tether net entanglement.

This study aims to assess the autonomous navigation performance of an asteroid orbiter enhanced using an inter-satellite link to a beacon satellite. Autonomous navigation includes the orbit determination of the orbiter and beacon, and asteroid gravity estimation without any ground station support. Navigation measurements were acquired using satellite-to-satellite tracking (SST) and optical observation of asteroid surface landmarks. This study presents a new orbiter–beacon SST scheme, in which the orbiter circumnavigates the asteroid in a low-altitude strongly-perturbed orbit, and the beacon remains in a high-altitude weakly-perturbed orbit. We used Asteroid 433 Eros as an example, and analyzed and designed low- and high-altitude orbits for the orbiter and beacon. The navigation measurements were precisely modeled, extended Kalman filters were devised, and observation configuration was analyzed using the Cramer–Rao lower bound (CRLB). Monte Carlo simulations were carried out to assess the effects of the orbital inclination and altitudes of the orbiter and beacon as key influencing factors. The simulation results showed that the proposed SST scheme was an effective solution for enhancing the autonomous navigation performance of the orbiter, particularly for improving the accuracy of gravity estimation.

Large spacecraft fall out of orbit and re-enter the atmosphere at the end of their lifetime, and they can break up into small debris upon re-entry. The spacecraft debris generated by the disintegration may lead to high risk when the surviving debris reaches the ground. One way to reduce the damage risk of spacecraft is to simulate the spacecraft disintegration process and accurately predict the falling area. Aerodynamics seriously affects the reentering process, especially in the continuous flow regime. Aerodynamic force and heat are the main factors leading to debris disintegration. High dynamic pressure leads to sharp changes in attitude and complex trajectories during debris fall. A numerical method based on an unstructured Cartesian grid was developed to simulate the disintegrating separation problem by coupling the Navier-Stokes equation and the six-degree-of-freedom trajectory equation. A method combining the numerical method for dynamic processes with numerical simulation based on a static aerodynamic/dynamic characteristic database was developed for forecasting the falling area. Spacecraft disintegrating separation from 60 km was simulated using the method, and the multibody aerodynamic interference and the separation trajectory were predicted. The falling process was forecast by a numerical simulation method based on the static aerodynamic database/dynamic characteristic database when the debris went out of the influence domain. This method has good forecasting efficiency while considering the aerodynamic interference, making it a valuable method for forecasting disintegrating separation and falling debris.

Currently, a surge in the number of spacecraft and fragments is observed, leading to more frequent breakup events in low Earth orbits (LEOs). The causes of these events are being identified, and specific triggers, such as collisions or explosions, are being examined for their importance to space traffic management. Backward propagation methods were employed to trace the origins of these types of breakup events. Simulations were conducted using the NASA standard breakup model, and satellite Hitomi’s breakup was analyzed. Kullback-Leibler (KL) divergences, Euclidean 2-norms, and Jensen-Shannon (JS) divergences were computed to deduce potential types of breakups and the associated fragmentation masses. In the simulated case, a discrepancy of 22.12 s between the estimated and actual time was noted. Additionally, the breakup of the Hitomi satellite was estimated to have occurred around UTC 1:49:26.4 on March 26, 2016. This contrasts with the epoch provided by the Joint Space Operation Center, which was estimated to be at 1:42 UTC ± 11 min. From the findings, it was suggested that the techniques introduced in the study can be effectively used to trace the origins of short-term breakup events and to deduce the types of collisions and fragmentation masses under certain conditions.

As an emerging approach to space situational awareness and space imaging, the practical use of an event-based camera (EBC) in space imaging for precise source analysis is still in its infancy. The nature of event-based space imaging and data collection needs to be further explored to develop more effective event-based space imaging systems and advance the capabilities of event-based tracking systems with improved target measurement models. Moreover, for event measurements to be meaningful, a framework must be investigated for EBC calibration to project events from pixel array coordinates in the image plane to coordinates in a target resident space object’s reference frame. In this paper, the traditional techniques of conventional astronomy are reconsidered to properly utilise the EBC for space imaging and space situational awareness. This paper presents the techniques and systems used for calibrating an EBC for reliable and accurate measurement acquisition. These techniques are vital in building event-based space imaging systems capable of real-world space situational awareness tasks. By calibrating sources detected using the EBC, the spatiotemporal characteristics of detected sources or “event sources” can be related to the photometric characteristics of the underlying astrophysical objects. Finally, these characteristics are analysed to establish a foundation for principled processing and observing techniques which appropriately exploit the capabilities of the EBC.

The deployment of mega constellations has had a significant effect on the compounding space debris environment, increasing the number of on-orbit objects in all conditions and damaging the stability of the space debris environment. The increased density of space objects is associated with an increased risk of on-orbit collisions. Collision risk exists not only between a mega constellation and the space debris environment but also inside a mega constellation. In this study, we used the Starlink constellation to investigate the self-induced collision risk caused by malfunctioning satellites. First, we analyzed the conjunction condition between malfunctioning and operative satellites based on long-term orbital evolution characteristics. The collision probability was then calculated based on the conjunction analysis results. The results show that malfunctioning satellites in Phase 1 cause an 86.2% self-induced collision probability based on a malfunctioning rate of 1%, which is close to the collision probability caused by objects larger than 6 cm during five years of service. Therefore, self-induced collisions are another important risk factor for the Starlink constellation.

Spacecraft conjunction management plays a crucial role in the mitigation of space collisions. When a conjunction event occurs, resources and time are spent analyzing, planning, and potentially maneuvering the spacecraft. This work contributes to a subpart of the problem: Confidently identifying events that will not lead to a high collision probability, and therefore do not require further investigation. The method reduces the dimensionality of the data via principal component analysis (PCA) on a subset of features. High-risk regions are then determined by clustering the projected data, and events that do not belong to a high-risk cluster are pruned. A genetic algorithm (GA) is developed to optimize the number of clusters and feature selection of the model. Furthermore, an ensemble learning framework is proposed to combine the suboptimal models for better generalization. The results show that the first set of parameters pruned approximately 50% of the events in the testing set with no false negatives, whereas the second set of parameters pruned 70% of the events and maintained a near-perfect recall. These results could benefit the optimization of operational resources and allow operators to focus better on the events of interest.