Astrodynamics最新文献

In this paper, a general recursive formulation of equations of motion is presented for open-loop gyroelastic multibody systems. The gyroelastic multibody system is defined as a multibody system with gyroelastic bodies, whereas a gyroelastic body is composed of a flexible body with a cluster of double-gimbal variable-speed control moment gyroscopes (DGVs). First, the motion equations of a single gyroelastic body are derived using Kane’s method. The influence of DGVs on the static moments, modal momentum coefficients, moments of inertia, modal angular momentum coefficients, and modal mass matrix for a flexible body are considered. The interactions between the DGVs and the flexibilities of the structures are captured. The recursive kinematic relations for a multibody system with different connections are then obtained from a flexible–flexible connection using a transformation matrix. The different connections contain a flexible–flexible connection, which represents a flexible body connecting to another flexible body, flexible–rigid and rigid–rigid connections. The recursive gyroelastic multibody dynamics are obtained by analyzing the kinematics of a multibody system and the dynamics of a single gyroelastic body. Numerical simulations are presented to verify the accuracy and efficiency of the proposed approach by comparing it with a direct formulation based on Kane’s method.

This work presents a new method for space-based angles-only orbit estimation. The approach relies on the integration of a novel and highly accurate Analytic Continuation technique with a new measurement model for multiple observers for inertial orbit estimation. Analytic Continuation computes the perturbed orbit dynamics, as well as the perturbed state transition matrix (STM), in the inertial frame. A new measurement model is developed for simultaneous measurements using a constellation of low-cost observers with monocular cameras for angles-only measurements. Analytic Continuation and the new measurement model are integrated in an Extended Kalman Filter (EKF) framework, where the Analytic Continuation method is used to propagate the perturbed dynamics and compute the perturbed STM and error covariance, with the measurements obtained via the new measurement model. Two case studies comprising small and large constellations of observers are presented, along with cases of sparse measurements and a study of the computational efficiency of the proposed approach. The results show that the new approach is capable of producing highly accurate and computationally efficient perturbed orbit estimation results compared with classical EKF implementations.

This study made use of a shape-based method to analyze the orbital dynamics of a spacecraft subject to a continuous propulsive acceleration acting along the circumferential direction. Under the assumption of a logarithmic spiral trajectory, an exact solution to the equations of motion exists, which allows the spacecraft state variables and flight time to be expressed as a function of the angular coordinate. There is also a case characterized by specific initial conditions in which the time evolution of the state variables may be analytically determined. In this context, the presented solution is used to analyze circle-to-circle trajectories, where the combination of two impulsive maneuvers and a logarithmic spiral path are used to accomplish the transfer. The determined results are then applied to the achievement of the Earth—Mars and the Earth—Venus transfers using actual data from a recent thruster developed by NASA.

The significant characteristics of space non-cooperative targets include the uncertainties of dynamic parameters and behaviors. Herein, a hybrid proximity control strategy adapted to the behavior uncertainty of a non-cooperative target is presented. First, the relative motion dynamics between the chaser and target is established in the geocentric inertial coordinate system and transcribed based on the chaser spacecraft body coordinate system. Subsequently, to facilitate proximity control under uncertain conditions, an extended state observer is designed to estimate and compensate for the total uncertainty in the relative motion dynamics. Finally, an event-triggered sliding mode control law is designed to track the target with behavior uncertainty and realize synchronization. Numerical simulations demonstrate the effectiveness of the proposed proximity control strategy for both tumbling and maneuvering targets.

Asteroid 469219 Kamo’oalewa, also named 2016 HO3, is a small-size fast-rotating near-Earth asteroid, which is a potential target for future explorations. Owing to its weak gravity and fast spin rate, the dynamics on the surface or in the vicinity of 2016 HO3 are significantly different from those of planets or other small bodies explored in previous missions. In this study, the geophysical and orbital environments of 2016 HO3 were investigated to facilitate a potential mission design. First, the geometric and geopotential topographies of 2016 HO3 were examined using different shape models. The lift-off and escape conditions on its fast-rotating surface were investigated. Then, the periodic orbits around 2016 HO3 were studied in the asteroid-fixed frame and the Sun—asteroid frame considering the solar radiation pressure. The stable regions of the terminator orbits were discussed using different parameters. Finally, the influence of the nonspherical shape on the terminator orbits was examined. The precise terminator orbits around a real shape model of 2016 HO3 were obtained and verified in the high-fidelity model. This study shows that the polar region of 2016 HO3 is the primary region for landing or sampling, and the terminator orbits are well suited for global mapping and measurements of 2016 HO3. The analysis and methods can also serve as references for the exploration of other small fast-rotating bodies.

In this study, a supervised machine learning approach called Gaussian process regression (GPR) was applied to approximate optimal bi-impulse rendezvous maneuvers in the cis-lunar space. We demonstrate the use of the GPR approximation of the optimal bi-impulse transfer to patch points associated with various invariant manifolds in the cis-lunar space. The proposed method advances preliminary mission design operations by avoiding the computational costs associated with repeated solutions of the optimal bi-impulsive Lambert transfer because the learned map is computationally efficient. This approach promises to be useful for aiding in preliminary mission design. The use of invariant manifolds as part of the transfer trajectory design offers unique features for reducing propellant consumption while facilitating the solution of trajectory optimization problems. Long ballistic capture coasts are also very attractive for mission guidance, navigation, and control robustness. A multi-input single-output GPR model is presented to represent the fuel costs (in terms of the ΔV magnitude) associated with the class of orbital transfers of interest efficiently. The developed model is also proven to provide efficient approximations. The multi-resolution use of local GPRs over smaller sub-domains and their use for constructing a global GPR model are also demonstrated. One of the unique features of GPRs is that they provide an estimate of the quality of approximations in the form of covariance, which is proven to provide statistical consistency with the optimal trajectories generated through the approximation process. The numerical results demonstrate our basis for optimism for the utility of the proposed method.

In this study, a novel approach based on the U-Net deep neural network for image segmentation is leveraged for real-time extraction of tracklets from optical acquisitions. As in all machine learning (ML) applications, a series of steps is required for a working pipeline: dataset creation, preprocessing, training, testing, and post-processing to refine the trained network output. Online websites usually lack ready-to-use datasets; thus, an in-house application artificially generates 360 labeled images. Particularly, this software tool produces synthetic night-sky shots of transiting objects over a specified location and the corresponding labels: dual-tone pictures with black backgrounds and white tracklets. Second, both images and labels are downscaled in resolution and normalized to accelerate the training phase. To assess the network performance, a set of both synthetic and real images was inputted. After the preprocessing phase, real images were fine-tuned for vignette reduction and background brightness uniformity. Additionally, they are down-converted to eight bits. Once the network outputs labels, post-processing identifies the centroid right ascension and declination of the object. The average processing time per real image is less than 1.2 s; bright tracklets are easily detected with a mean centroid angular error of 0.25 deg in 75% of test cases with a 2 deg field-of-view telescope. These results prove that an ML-based method can be considered a valid choice when dealing with trail reconstruction, leading to acceptable accuracy for a fast image processing pipeline.

The collision probability computation of space objects plays an important role in space situational awareness, particularly for conjunction assessment and collision avoidance. Early works mainly relied on Monte Carlo simulations to predict collision probabilities. Although such simulations are accurate when a large number of samples are used, these methods are perceived as computationally intensive, which limits their application in practice. To overcome this limitation, many approximation methods have been developed over the past three decades. This paper presents a comprehensive review of existing space-object collision probability computation methods. The advantages and limitations of different methods are analyzed and a systematic comparison is presented. Advice regarding how to select a suitable method for different short-term encounter scenarios is then provided. Additionally, potential future research avenues are discussed.

Small bodies in the solar system are known to be covered by a layer of loose unconsolidated soil composed of grains ranging from dusty sands to rugged boulders. Various geophysical processes have modified these regolith layers since their origin. Therefore, the landforms on regolith-blanketed surfaces hold vital clues for reconstructing the geological processes occurring on small bodies. However, the mechanical strength of small body regolith remains unclear, which is an important parameter for understanding its dynamic evolution. Furthermore, regolith mechanical properties are key factors for the design and operation of space missions that interact with small body surfaces. The granular penetrometer, which is an instrument that facilitates in situ mechanical characterization of surface/subsurface materials, has attracted significant attention. However, we still do not fully understand the penetration dynamics related to granular regolith, partially because of the experimental difficulties in measuring grain-scale responses under microgravity, particularly on the longer timescales of small body dynamics. In this study, we analyzed the slow intrusion of a locomotor into granular matter through large-scale numerical simulations based on a soft sphere discrete element model. We demonstrated that the resistance force of cohesionless regolith increases abruptly with penetration depth after contact and then transitions to a linear regime. The scale factor of the steady-state component is roughly proportional to the internal friction of the granular materials, which allows us to deduce the shear strength of planetary soils by measuring their force-depth relationships. When cohesion is included, due to the brittle behavior of cohesive materials, the resistance profile is characterized by a stationary state at a large penetration depth. The saturation resistance, which represents the failure threshold of granular materials, increases with the cohesion strength of the regolith. This positive correlation provides a reliable tool for measuring the tensile strength of granular regolith in small body touchdown missions.