Astronautics doi: 10.3390/astronautics1030013

Authors: Kun Zhang Yanping Zhou Yunhan He Yun Xu

It is challenging to detect continuous low-thrust maneuver parameters of non-cooperative satellites because the signals are weak over limited observation arcs and are readily masked by measurement noise and orbit-determination errors. This paper proposes a conditional diffusion model for detecting and estimating continuous low-thrust maneuver parameters from relative-orbit observations. The method uses relative-orbit observations of the non-cooperative target to construct conditional inputs that incorporate orbital dynamical priors. Single-step differencing and dimensionless processing are then used to strengthen weak maneuver signatures. The conditional diffusion model learns the evolution of maneuver parameters under noisy conditions and estimates three-axis continuous low-thrust acceleration sequences. Based on simulations considering the Gaussian noise of relative positions and velocities, the proposed method achieved 85.2% maneuver detection accuracy, while that of the batch least-squares benchmark method was 67.8%. The proposed method is simulated and verified based on Sentinel-6A. Results show that the continuous low-thrust maneuver can be robustly identified under low signal-to-noise ratios and the temporal parameter evolution can be recovered. The method provides a practical route for analyzing non-cooperative satellite maneuver and supporting on-orbit space situational awareness.

Astronautics doi: 10.3390/astronautics1030012

Authors: Yunxiao Yang Feng Yu Jiaxin Liu

The spacecraft reachable domain has become increasingly important for orbital game analysis due to growing on-orbit activities such as servicing, debris removal, and space situational awareness. This paper provides a comprehensive review of reachable domain theory and its applications in orbital games. A unified mathematical framework is established through three complementary classification dimensions: spatial attributes that distinguish absolute from relative reachable domains, temporal attributes that differentiate free-time from fixed-time reachable domains, and informational attributes that contrast deterministic and predictive reachable domains. Solution methods are systematically reviewed according to this taxonomy, covering analytical and semi-analytical methods, numerical optimization approaches, and geometric and sampling methods for spatial-scale reachable domains, as well as linearized ellipsoidal approximation, exact envelope determination, and fast analytical approximation for time-scale reachable domains. Applications are examined through three representative scenarios: one-on-one pursuit-evasion games, multi-agent cooperative games, and threat-avoidance and defense games. Key limitations of existing approaches are identified, including modeling fidelity, computational efficiency, and scalability under uncertainty. Future research directions are outlined to address these challenges.

Astronautics doi: 10.3390/astronautics1030011

Authors: Chandan Sheikder Weimin Zhang Xiaopeng Chen Shicheng Fan Tairan Li Haotong He

Martian dust storms cut off communication and break standard robot navigation. We built a hybrid system that keeps robot swarms alive during these blackouts and recovers their data quickly. Our rovers use Spiking Neural Networks (SNNs) on their own edge processors to navigate without a signal. Once the storm passes, we use the Quantum Approximate Optimization Algorithm (QAOA) on a cloud platform to merge the fragmented maps the rovers collected while they were offline. We tested this system in a Robot Operating System 2 (ROS 2) and Gazebo environment using a simulated 10-rover Martian deployment. During the simulated blackout, our SNN edge navigation achieved a 92.0% survival rate, outperforming traditional planners like Dynamic Window Approach (DWA) (29.0%) and Timed Elastic Band (TEB) (24.3%). The neuromorphic approach also reduced overall system power consumption by 80.0% compared to a traditional unoptimized Graphics Processing Unit (GPU)-based Simultaneous Localization and Mapping (SLAM) baseline. For the map recovery phase, our simulated QAOA proof-of-concept evaluated the map constraints in just 1.2 ms, compared to 50.0 ms for a classical Generalized Iterative Closest Point (G-ICP) and g2o pose-graph approach. Despite the noisy sensor data collected during the blackout, the final quantum-stitched map achieved an 8.54 cm Root Mean Square Error (RMSE). These results show that combining edge-based neuromorphic processing with quantum cloud computing secures swarm survival and accelerates post-disaster data recovery for deep-space missions.

Astronautics doi: 10.3390/astronautics1020010

Authors: Lisong Hao Taibo Li Hongwei Liu

In commercial aerospace flight-style launch scenarios, multiple parallel missions impose tight constraints, multiple objectives, and highly dynamic conditions on TT&C (Telemetry, Tracking, and Command) resource scheduling. This paper studies coordinated scheduling of TT&C equipment and sites. First, a multi-objective model is formulated that considers equipment–type matching, time-window constraints, mobile-equipment transfer paths, and coverage requirements. The model enforces coverage thresholds for all mission arc segments, while minimizing (i) the total travel distance of mobile equipment and (ii) the number of mobile units deployed. Second, to obtain high-quality feasible solutions quickly, an improved greedy scheduling algorithm is proposed. The algorithm processes tasks in chronological order and makes locally optimal decisions. It prioritizes fixed equipment and then selects mobile equipment by minimizing transfer distance under time-feasibility constraints. Finally, experiments on simulated scenarios demonstrate the effectiveness of the proposed method. The algorithm produces feasible schedules that satisfy coverage requirements in an extremely short time. It also provides a good initial solution for subsequent refinement, which makes it suitable for dynamic scheduling that requires real-time responsiveness.

Astronautics doi: 10.3390/astronautics1020009

Authors: Wenchi Zhao Jixin Ding Xue Bai Jun Jiang Tao Nie Ming Xu

As a crucial initial step in humanity’s quest to explore deep space, lunar transfer missions have garnered significant attention. The escalating demand for increased payload capacity and mission flexibility have presented challenges in terms of mission fuel costs. In response, the design of low-energy lunar transfer trajectories, rooted in multibody dynamics, has become paramount for deep space exploration trajectory design. This paper summarizes the design methods for transfer trajectories from the Earth to the Moon and even deeper space that consume low energy at the expense of expanded transfer time. The fundamental design methods include the weak stability boundary method, the chaos control method, and the invariant manifold theory, which are primarily determined by dynamical mechanisms. Additionally, the paper discusses the low-thrust technique, formulating trajectory design as an optimization problem to tailor thrust profiles for minimum fuel consumption. Finally, landmark missions are discussed to demonstrate the practical applications and advantages of low-energy trajectories, spanning lunar missions to exploration within deeper space regions.

Astronautics doi: 10.3390/astronautics1010008

Authors: Yilin Zou Fanghua Jiang

Direct collocation transcription is a dominant technique for solving complex optimal control problems, converting continuous dynamics into large-scale, sparse nonlinear programming problems. The computational efficiency of this approach is fundamentally limited by the evaluation of first- and second-order derivatives required by modern optimization algorithms. While general-purpose automatic differentiation tools exist, they often fail to fully exploit the repetitive substructure inherent in trajectory discretization. This paper presents a vectorized, sparse, second-order forward automatic differentiation framework specifically tailored for direct collocation methods. By explicitly distinguishing between scalar and vector nodes within the expression graph, the proposed method leverages the independence of mesh point evaluations to enable Single Instruction, Multiple Data (SIMD) execution and optimize memory access patterns. This structure-aware approach ensures linear time complexity with respect to the number of discretization nodes while maintaining the flexibility to handle complex dependencies. The methodology is implemented in the open-source software package pockit and is validated through three distinct engineering case studies: the aggressive stabilization of a nano-quadrotor, the powered descent guidance of a reusable launch vehicle, and a low-thrust heliocentric orbital transfer. These applications demonstrate the framework’s capability to deliver high-performance derivative computation for large-scale, nonlinear dynamical systems.

Astronautics doi: 10.3390/astronautics1010007

Authors: Simon Evetts Beth Healey Tessa Morris-Paterson Vladimir Pletser

The rapid expansion of commercial human spaceflight is forcing a re-examination of how we decide who is “fit to fly” in space. For more than six decades, astronaut selection has been dominated by government programmes employing stringent medical and psychological criteria designed to minimise risk for small cohorts undertaking long-duration, high-consequence missions. Contemporary standards such as NASA-STD-3001 reflect this paradigm, treating astronauts as highly trained national assets expected to perform reliably under extreme physiological and psychological stress. In contrast, commercial operators aim to fly large numbers of spaceflight participants with highly heterogeneous medical and psychological profiles, within regulatory frameworks that emphasise informed consent and currently impose very limited prescriptive health requirements on passengers. This review examines the evolution and structure of traditional astronaut selection, outlines emerging approaches to screening and certifying commercial spaceflight customers, and explores the conceptual and practical gap between “selection” and “screening”. Particular attention is given to the increasing relevance of behavioural and psychological risk in short-duration but high-stress commercial missions, where acute responses, passenger–crew interaction, and behavioural variability can influence safety, especially in mixed-capability crews. Drawing on agency standards, psychological selection research, and recent proposals for commercial medical guidelines, this paper proposes a risk-informed, mission- and role-specific framework that adapts lessons from government astronaut corps to the needs of commercial spaceflight. We argue that future practice must balance safety, inclusion, and commercial viability through proportionate, evidence-based risk management, supported by systematic data collection across government and commercial flights.

Astronautics doi: 10.3390/astronautics1010006

Authors: Zhong Zhang Niccolò Michelotti Gonçalo Oliveira Pinho Yilin Zou Francesco Topputo

This paper presents a comparative study of the applicability and accuracy of optimal control methods and neural-network-based estimators in the context of porkchop plots for preliminary asteroid rendezvous mission design. The scenario considered involves a deep-space CubeSat equipped with a low-thrust engine, departing from Earth and rendezvousing with a near-Earth asteroid within a three-year launch window. A low-thrust trajectory optimization model is formulated, incorporating variable specific impulse, maximum thrust, and path constraints. The optimal control problem is efficiently solved using Sequential Convex Programming (SCP) combined with a solution continuation strategy. The neural network framework consists of two models: one predicts the minimum fuel consumption (Δv), while the other estimates the minimum flight time (Δt) which is used to assess transfer feasibility. Case results demonstrate that, in simplified scenarios without path constraints, the neural network approach achieves low relative errors across most of the design space and successfully captures the main structural features of the porkchop plots. In cases where the SCP-based continuation method fails due to the presence of multiple local optima, the neural network still provides smooth and globally consistent predictions, significantly improving the efficiency of early-stage asteroid candidate screening. However, the deformation of the feasible region caused by path constraints leads to noticeable discrepancies in certain boundary regions, thereby limiting the applicability of the network in detailed mission design phases. Overall, the integration of neural networks with porkchop plot analysis offers an effective decision-making tool for mission designers and planetary scientists, with significant potential for engineering applications.

Astronautics doi: 10.3390/astronautics1010005

Authors: Lingyun Gu Qingyun Fang Eugene Popov Vitalii Pavlov Sergey Volvenko Sergey Makarov Ge Dong

Remote sensing object detection is a critical task in Earth observation. Despite the remarkable progress made in general object detection, existing detectors struggle with remote sensing scenarios due to the prevalence of numerous small objects with limited discriminative cues. Cutting-edge studies have shown that incorporating contextual information effectively enhances the detection performance for small objects. Meanwhile, recent research has revealed that convolution in the frequency domain is capable of capturing long-range spatial dependencies with high efficiency. Inspired by this, we propose a Frequency-aware Feature Pyramid Framework (FFPF) for remote sensing object detection, which consists of a novel Frequency-aware ResNet (F-ResNet) and a Bilateral Spectral-aware Feature Pyramid Network (BS-FPN). Specifically, the F-ResNet is proposed to extract the spectral context information by plugging the frequency domain convolution into each stage of the backbone, thereby enriching features of small objects. In addition, the BS-FPN employs a bilateral sampling strategy and skipping connection to model the association of object features at different scales, enabling the contextual information extracted by the F-ResNet to be fully leveraged. Extensive experiments are conducted for object detection in the public remote sensing image dataset and natural image dataset. The experimental results demonstrate the excellent performance of the FFPF, achieving 73.8% mAP on the DIOR dataset without using any additional training tricks.

Astronautics doi: 10.3390/astronautics1010004

Authors: Zhengqing Fang Roberto Armellin Yingkai Cai

Low-thrust propulsion systems have become mainstream for Low Earth Orbit (LEO) satellites due to their superior propellant efficiency, yet conventional low-thrust transfer strategies suffer from high computational costs and failure to achieve full orbital element convergence. To address these drawbacks, this paper proposes a novel semi-analytical three-phase low-thrust transfer strategy that leverages J2 gravitational precession to realize convergence of all orbital elements for circular orbits. The core of the method lies in the design of two symmetric thrust arcs and an intermediate coasting period that utilizes J2 precession. By solving the resulting polynomial equation, the strategy achieves simultaneous controlled convergence of the Right Ascension of the Ascending Node (RAAN) and the argument of latitude (AOL). Simulation results demonstrate that the proposed method achieves significant fuel savings compared to direct transfer strategies, while simultaneously achieving superior computational speed. Extensive validation via 100,000 Monte Carlo simulations confirms the method’s scope of applicability, and the sufficient conditions for the existence of a solution are provided. It is further found that the proposed method is particularly well-suited for missions involving medium-to-high inclination orbits and large RAAN gaps, such as constellation deployment. In conclusion, this strategy provides a fuel-efficient and computationally fast solution for low-thrust transfer, establishing the basis for the operational management of future large-scale space systems equipped with low-thrust propulsion.

Astronautics doi: 10.3390/astronautics1010003

Authors: Paulo Hercilio Viegas Rodrigues Guilherme Bovi Ambrosano

Plant species sensitive to desiccation or vegetatively propagation are difficult to store and transport in the germplasm for space travel. Applying plant tissue culture can help to create a Plant Germplasm Bank for this species. For this purpose, the Compact Growth Chamber (CGC) was created to store and transport in vitro explants, maintaining them for long periods in Slow-Grown Storage (SGS). Explants under SGS have reduced growth metabolism to complete space missions. This study aimed to evaluate the CGC efficacy in the long term of in vitro storage of explant of Taioba (Xanthosoma sagittifolium), a tropical species that vegetatively propagates and has high nutritional value. For this, three CGCs were connected, side by side, with different LED light spectra (CGC1: Red spectrum; CGC2: 50% Red + 50% Blue spectra-control; CGC3: Blue spectrum), each one containing nine test tubes with taioba explants (one per test tube), and LED lights intensity adjusted for 30 µmol m−2 s−1. The CGCs were maintained for 120 days in the darkroom, at 25 ± 2 °C temperature and 50–60% humidity, and, at the end, the growth and morphological parameters of taioba plantlets were evaluated. These results demonstrate that the explant storage in CGC3 showed lower root numbers and root lengths than in CGC1 and CGC2. In addition, the Blue spectrum in CGC3 reduced the root oxidation and browning, resulting in 100% live explants. This study provides that the CGC fulfilled its proposed function of transporting and storing the in vitro explants for space travel.

Astronautics doi: 10.3390/astronautics1010002

Authors: Zhaokui Wang

Since the dawn of civilization, humanity has gazed at the stars with wonder and longing [...]

Astronautics doi: 10.3390/astronautics1010001

Authors: Lin Li

When humanity first broke free from Earth’s gravitational bonds, we began the grandest chapter in the history of our civilization [...]