Astrodynamics最新文献

Relative navigation is crucial for spacecraft noncooperative rendezvous, and angles-only navigation using visible and infrared cameras provides a feasible solution. Herein, an angles-only navigation algorithm with multisensor data fusion is proposed to derive the relative motion states between two noncooperative spacecraft. First, the design model of the proposed algorithm is introduced, including the derivation of the state propagation and measurement equations. Subsequently, models for the sensor and actuator are introduced, and the effects of various factors on the sensors and actuators are considered. The square-root unscented Kalman filter is used to design the angles-only navigation filtering scheme. Additionally, the Clohessy—Wiltshire terminal guidance algorithm is introduced to obtain the theoretical relative motion trajectories during the rendezvous operations of two noncooperative spacecraft. Finally, the effectiveness of the proposed angles-only navigation algorithm is verified using a semi-physical simulation platform. The results prove that an optical navigation camera combined with average accelerometers and occasional orbital maneuvers is feasible for spacecraft noncooperative rendezvous using angles-only navigation.

Real-time guidance is critical for the vertical recovery of rockets. However, traditional sequential convex optimization algorithms suffer from shortcomings in terms of their poor real-time performance. This work focuses on applying the deep learning-based closed-loop guidance algorithm and error propagation analysis for powered landing, thereby significantly improving the real-time performance. First, a controller consisting of two deep neural networks is constructed to map the thrust direction and magnitude of the rocket according to the state variables. Thereafter, the analytical transition relationships between different uncertainty sources and the state propagation error in a single guidance period are analyzed by adopting linear covariance analysis. Finally, the accuracy of the proposed methods is verified via a comparison with the indirect method and Monte Carlo simulations. Compared with the traditional sequential convex optimization algorithm, our method reduces the computation time from 75 ms to less than 1 ms. Therefore, it shows potential for online applications.

The dynamics of a spacecraft propelled by a continuous radial thrust resembles that of a nonlinear oscillator. This is analyzed in this work with a novel method that combines the definition of a suitable homotopy with a classical perturbation approach, in which the low thrust is assumed to be a perturbation of the nominal Keplerian motion. The homotopy perturbation method provides the analytical (approximate) solution of the dynamical equations in polar form to estimate the corresponding spacecraft propelled trajectory with a short computational time. The accuracy of the analytical results was tested in an orbital-targeting mission scenario.

Space object observation requirements and the avoidance of specific attitudes produce pointing constraints that increase the complexity of the attitude maneuver path-planning problem. To deal with this issue, a feasible attitude trajectory generation method is proposed that utilizes a multiresolution technique and local attitude node adjustment to obtain sufficient time and quaternion nodes to satisfy the pointing constraints. These nodes are further used to calculate the continuous attitude trajectory based on quaternion polynomial interpolation and the inverse dynamics method. Then, the characteristic parameters of these nodes are extracted to transform the path-planning problem into a parameter optimization problem aimed at minimizing energy consumption. This problem is solved by an improved hierarchical optimization algorithm, in which an adaptive parameter-tuning mechanism is introduced to improve the performance of the original algorithm. A numerical simulation is performed, and the results confirm the feasibility and effectiveness of the proposed method.

This study investigated periodic coupled orbit—attitude motions within the perturbed circular restricted three-body problem (P-CRTBP) concerning the perturbations of a radiated massive primary and an oblate secondary. The radiated massive primary was the Sun, and each planet in the solar system could be considered an oblate secondary. Because the problem has no closed-form solution, numerical methods were employed. Nevertheless, the general response of the problem could be non-periodic or periodic, which is significantly depended on the initial conditions of the orbit-attitude states. Therefore, the simultaneous orbit and attitude initial states correction (SOAISC) algorithm was introduced to achieve precise initial conditions. On the other side, the conventional initial guess vector was essential as the input of the correction algorithm and increased the probability of reaching more precise initial conditions. Thus, a new practical approach was developed in the form of an orbital correction algorithm to obtain the initial conditions for the periodic orbit of the P-CRTBP. This new proposed algorithm may be distinguished from previously presented orbital correction algorithms by its ability to propagate the P-CRTBP family orbits around the Lagrangian points using only one of the periodic orbits of the unperturbed CRTBP (U-CRTBP). In addition, the Poincaré map and Floquet theory search methods were used to recognize the various initial guesses for attitude parameters. Each of these search methods was able to identify different initial guesses for attitude states. Moreover, as a new innovation, these search methods were applied as a powerful tool to select the appropriate inertia ratio for a satellite to deliver periodic responses from the coupled model. Adding the mentioned perturbations to the U-CRTBP could lead to the more accurate modeling of the examination environment and a better understanding of a spacecraft’s natural motion. A comparison between the orbit-attitude natural motions in the unperturbed and perturbed models was also conducted to show this claim.

To rapidly model the gravity field near elongated asteroids, an intelligent inversion method using Hopfield neural networks (HNNs) is proposed to estimate on-orbit simplified model parameters. First, based on a rotating mass dipole model, the gravitational field of asteroids is characterized using a few parameters. To solve all the parameters of this simplified model, a stepped parameter estimation model is constructed based on different gravity field models. Second, to overcome linearization difficulties caused by the coupling of the parameters to be estimated and the system state, a dynamic parameter linearization technique is proposed such that all terms except the parameter terms are known or available. Moreover, the Lyapunov function of the HNNs is matched to the problem of minimizing parameter estimation errors. Equilibrium values of the Lyapunov function are used as estimated values. The proposed method is applied to natural elongated asteroids 216 Kleopatra, 951 Gaspra, and 433 Eros. Simulation results indicate that this method can estimate the simplified model parameters rapidly, and that the estimated simplified model provides a good approximation of the gravity field of elongated asteroids.

Stable or nearly stable orbits do not generally possess well-distinguished manifold structures that assist in designing trajectories for departing from or arriving onto a periodic orbit. For some potential missions, the orbits of interest are selected as nearly stable to reduce the possibility of rapid departure. However, the linearly stable nature of these orbits is also a drawback for their timely insertion into or departure from the orbit. Stable or nearly stable near rectilinear halo orbits (NRHOs), distant retrograde orbits (DROs), and lunar orbits offer potential long-horizon trajectories for exploration missions and demand efficient operations. The current investigation focuses on leveraging stretching directions as a tool for departure and trajectory design applications. The magnitude of the state variations along the maximum stretching direction is expected to grow rapidly and, therefore, offers information for efficient departure from the orbit. Similarly, maximum stretching in reverse time enables arrival with a minimal maneuver magnitude.