Advances in Astronautics Science and Technology最新文献

With the rapid development of human space technology, space photography is increasingly being applied to tasks such as satellite observation, debris collection, and deep-space exploration. However, extreme space environments and inherent deviations of imaging systems may lead to the accumulation of degradations, not only results in low-quality imaging results, but also hampers the performance of downstream applications such as object detection, tracking, and attitude estimation. Under extreme space imaging conditions, we focus on four key image enhancement tasks, including image denoising, deblurring, super-resolution and multi-exposure image fusion. We review the classic and deep learning-based methods, summarize the characteristics and analyze the practical problems in the space imaging process. The paper also presents timelines of method development and lists databases for training, validating and testing, providing a comprehensive overview and a reference for research on extreme space image enhancement. Furthermore, we discuss critical directions that need to be addressed in the future to advance new technologies for high-resolution imaging in extreme space environments.

In this paper, to satisfy the impact angle constraint, a general formulation of the biased proportional navigation guidance is provided. The proposed guidance law is built on the missile-target distance domain (range domain) rather than time domain, which can enhance the guidance accuracy without estimating the flight time. The capture region of the proposed guidance law is fully investigated for all desired impact angles between (pm 180^circ) by studying the behavior of the look angle. The result can provide guidelines on the selection of the desired impact angle based on the initial conditions. For larger impact angles scenarios where the look angle does not converge to zero, the proposed guidance law is readily modified to fulfill the guidance objectives. Numerical simulation results are in complete agreement with theoretical analysis.

To tackle the challenges posed by disturbances and uncertainties in helicopters, this article introduces a neural-network-based anti-disturbance integral sliding mode control method. The proposed methodology employs feedback linearization technique to mitigate the nonlinear characteristics of the helicopter altitude and attitude system, thereby enabling the effective design of an integral sliding surface. To comprehensively handle both external disturbances and system uncertainties, the control architecture integrates a dual-observer system comprising a nonlinear disturbance observer and a neural network observer. The proposed control method enhances system robustness, demonstrating superior performance over traditional sliding mode control methods through faster response time and reduced chattering effects. The control system’s stability is conclusively demonstrated through Lyapunov stability theory. The simulation results confirm that our proposed method effectively improves system stability and robustness across diverse conditions.

The dynamic characteristics and jet atomization performance of liquid rocket engine injectors are of great significance for the stable operation of liquid rocket engines. This paper provides a review of the dynamic characteristics of liquid rocket engine injectors and the study of spray field dynamics. Firstly, the role of injectors in the spray and combustion of engine combustor was overviewed. Then, theoretical researches on the dynamic characteristics of various typical injectors were discussed. Subsequently, experimental studies on the dynamic characteristics of injectors under atmospheric pressure, backpressure, and trans-/supercritical conditions were discussed. After that, the research progress on the spray field dynamics under unsteady inflow conditions and under external field excitation were elaborated. Finally, a summary was made and suggestions were proposed for future research. It is urgent to expand the injector dynamics theory to the field of cryogenic fluids under trans-/supercritical conditions in the future. The dynamic characteristics of injection and combustion of cryogenic fluids (such as liquid nitrogen, liquid oxygen, liquid hydrogen, methane, etc.) for trans-/supercritical conditions during incoming flow pulsation need to be studied. A more systematic and comprehensive theoretical study should be conducted on the unsteady atomization problem of gas–liquid coaxial injectors.

On-orbit servicing (OOS) is a comprehensive technology that provides functional recovery, performance enhancement, assembly and manufacturing of new spacecraft, or removal of orbital debris to other spacecrafts, and it is the forefront technology direction of the current development in the aerospace field. Since the Mission Extension Vehicle (MEV) successfully implemented the takeover-based life extension in orbit, it marks that on-orbit servicing technologies have been in a critical stage of transformation from technology validation to practical application. It is expected that a variety of on-orbit servicing application modes will be generated in the future and have a far-reaching impact on the design, development and operation of spacecrafts. This paper summarizes the current development status of on-orbit servicing technologies, analyzes several key technologies requirements of practical application scenarios, and provides an outlook on the future development trends.

In order to enhance the combustion of fuel and air in scramjet combustor, numerical simulation of scramjet combustor with five different wall divergence angles and five different wall divergence positions was carried out. Unsteady Reynolds-averaged Navier-Stokes equations and shear stress transport k-ω turbulence model are used to deal with turbulence, and finite rate/eddy dissipation model combined with global reaction mechanism is used to deal with turbulent-chemistry interaction. Firstly, the reliability of numerical simulation method is verified and validated by grid independent study and experimental case study. Then the results of shock wave system, recirculation region, Mach number, pressure, temperature, component mass fraction, combustion efficiency and total pressure loss under different wall divergence are obtained by numerical simulation, which fully reflects the influence of wall divergence on combustor performance. The results show that with the increase of divergence angle, the intensity of shock wave system in the flow field weakens, the combustion efficiency decreases gradually, and the total pressure loss decreases gradually. There exist some small divergence angle at which the combustion efficiency is high and the total pressure loss is relative low. For the divergence position, when it is slightly shifted downstream from the reference position, the combustor maintains favorable performance. When the rearward shift of the divergence position increases to a large value, the combustion efficiency increases significantly, but the total pressure loss also increases remarkably, and thermal choking may occur, so the rearward shift of the divergence position should not be too large.

The composite manufacturing laser inertial navigation system has a complex instrument configuration and high power consumption. It adopts a structure-circuit integrated design manufacturing method, which results in a compact structure and a small heat dissipation area, leading to inconsistent startup characteristics of the instrument in different temperature environments. Parameter modeling and compensation based on the traditional single-traverse calibration test method from low to high temperature are difficult to adapt to different temperature environmental conditions, resulting in poor compensation effects. In this study, combining practical usage conditions, a rapid calibration method for startup under different temperature insulation conditions is employed to identify instrument parameters. A system-level global modeling method based on the Gaussian Regression Process (GPR) is utilized, and the hyperparameters of the kernel function are optimized using the Grey Wolf Optimization (GWO) algorithm. Compared with GPR and polynomial fitting methods, its fitting performance and compensation effect are superior. Through precision testing of the inertial navigation system in different temperature environments, the accuracy of the gyroscope improved from 0.0084(^{circ })/h to 0.0024(^{circ })/h, and the accuracy of the accelerometer improved from 99.1ppm to 2.74ppm, validating the effectiveness of the temperature compensation method.

This paper addresses the issue of attitude control for dual-control aircraft with model uncertainty, presenting a novel adaptive model-free sliding mode control (ASMMFC) algorithm based on long-short-term memory (LSTM) neural network. In comparison to existing adaptive sliding mode control algorithms utilizing neural networks, ASMMFC relaxes the underlying assumptions, thus broadening its scope of applicability. In the process of control law design, the LSTM neural network is used to fit the system term, so that it no longer depends on the prior information of the model. The online update law of neural network weights is derived by the Lyapunov method, and the stability of the system is proved. In the simulation process, the ASMMFC is applied to the aircraft attitude control scenario with model uncertainty and time-varying parameters. Simulation results show that the performance of the ASMMFC is better than other existing adaptive sliding mode control methods.

The elevated intracranial pressure under microgravity conditions will lead to the variation of physical structure and physiological behavior of brain cells. In this work, a three-dimensional numerical simulation model of BV-2 cells adhered to the substrate with different morphologies is constructed, the cell deformation under typical space microgravity conditions is simulated and the cell function response under corresponding conditions are experimentally analyzed. The mechanical properties of cells are obtained by atomic force microscopy testing. The effects of cell height and intracranial pressure which corresponds to certain microgravity condition on the cell deformation are clarified. The results demonstrate that the model can accurately calculate both the mechanical and displacement responses of the cell following a change in external pressure. This simulation enables the prediction of the concentration area of the stress, the amount of deformation and the potential risk of rupture of adherent cells with different morphologies under varying pressures.

This paper addresses the task assignment problem for a geodesic dome phased array antenna (GDPAA), which is described as an optimization problem to obtain the maximum measurement performance. Several critical challenges arise in this task allocation, including the high dimensionality of decision variables, multiple conflicting objectives, and the lack of an analytical expression for the objective function. To solve these challenges, this work proposes a high-dimensional combinatorial Bayesian optimization approach for this task scheduling. A random dimension reduction method is used to simplify the decision variables to handle large-scale tasks. With the consideration on the time complexity of the construction of the classical surrogate model for Bayesian optimization, a probabilistic surrogate model is built to describe the relationship between the measurement task and the GDPAA’s performance. The new strategy accelerates the algorithm convergence. An experiment is conducted to show the merit of effectiveness of the proposed method. Compared to reinforcement learning, particle swarm optimization, and other methods, the proposed approach achieves superior measurement performance with reduced computational time.