Next Issue
Volume 13, April
Previous Issue
Volume 13, February
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.0
2.2
Journals
Aerospace
Volume 13
Issue 3
share announcement

Aerospace, Volume 13, Issue 3 (March 2026) – 92 articles

Cover Story (view full-size image): The ever-growing number of debris comprising rocket bodies and defunct satellites in orbit around the Earth has shifted the interest of space agencies towards the development of reliable GNC systems for non-cooperative rendezvous missions. Such efforts demand on-board software solutions to enable the servicer spacecraft to autonomously approach the client in a safe manner. Within this context, the current study details the design and validation of a rule-based guidance architecture that leverages existing closed-form impulsive maneuvering schemes and extends their formulation to arbitrarily elliptic orbits. The results show that the proposed design can feasibly be used as a general baseline across different mission scenarios. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
31 pages, 26847 KB  
Article
Harmonic Frequency Analysis of Asynchronous Motion in a Rubbing Rotor System with Flexible Casing Constraint
by Di Liu, Xingen Lu and Yinli Feng
Aerospace 2026, 13(3), 298; https://doi.org/10.3390/aerospace13030298 - 23 Mar 2026
Viewed by 212
Abstract
Rotor-flexible casing rubbing can induce strong nonlinear dynamics in rotor systems. This study investigates the harmonic frequency characteristics of a rubbing rotor system with a flexible casing constraint. A nonlinear rub-impact model combined with a finite element-based rotor–casing coupling framework is developed to [...] Read more.
Rotor-flexible casing rubbing can induce strong nonlinear dynamics in rotor systems. This study investigates the harmonic frequency characteristics of a rubbing rotor system with a flexible casing constraint. A nonlinear rub-impact model combined with a finite element-based rotor–casing coupling framework is developed to evaluate system responses under concentric and eccentric configurations. The harmonic components of rotor and casing vibrations are analyzed over a range of rotational speeds. Results show that, under concentric conditions, harmonic frequencies originate from rubbing-induced asynchronous motion. The harmonic sub-frequencies observed in the spectrum correspond to lobed rotor orbits formed during the transition from synchronous to asynchronous motion under continuous rubbing forces. Under eccentric rotor–casing alignment, the vibration spectrum becomes more complex and exhibits frequency clustering. The results provide insight into harmonic generation mechanisms and highlight the role of casing flexibility in rubbing-induced asynchronous motion. Full article
(This article belongs to the Special Issue Aircraft Structural Dynamics)
►▼ Show Figures

Figure 1

84 pages, 13153 KB  
Review
Review of Rotary-Wing Morphing Actuation Systems
by Mars Burke and Alvin Gatto
Aerospace 2026, 13(3), 297; https://doi.org/10.3390/aerospace13030297 - 23 Mar 2026
Viewed by 4322
Abstract
A review of morphing actuation systems in relation to rotary-wing aerial platforms is presented. The research highlights an inadequate maturation of rotary actuation systems, characterised by a scarcity of (1) comprehensive full-scale experimental research relative to non-rotary (fixed-wing) systems, (2) techniques used for [...] Read more.
A review of morphing actuation systems in relation to rotary-wing aerial platforms is presented. The research highlights an inadequate maturation of rotary actuation systems, characterised by a scarcity of (1) comprehensive full-scale experimental research relative to non-rotary (fixed-wing) systems, (2) techniques used for rotary actuation systems and (3) implementation of full-chord morphing systems, with existing research only utilising partial-chord actuation techniques. Additionally, another notable shortcoming is presented to be the lack of comprehensive proportional investigation in the proposed five-step development process for rotary actuation designs. A comprehensive critical review is offered, covering the following challenges of progressing through this development process for rotary actuation systems from conceptual design to production: (1) numerical and computational studies, (2) small-scale wind-tunnel testing, (3) full-scale wind-tunnel testing, (4) demonstrator, and ultimately (5) fabrication for industrial implementation. The review examines several existing rotary actuation systems, including (but not limited to) leading-edge, trailing-edge and Gurney flaps; active twist; chord extension; variable span and camber systems. Comparisons are made between rotary morphing actuation systems and their non-morphing counterparts, highlighting the distinct difficulties encountered by rotary-wing systems due to the more complex and challenging operational conditions found in rotorcraft. The review reveals that a significant portion of existing research on rotary-wing systems has focused only on early-stage development, including computational modelling and sub-scale wind-tunnel experiments, underscoring the necessity for more comprehensive full-scale testing and prototype evaluation given that only a small number of studies have progressed to full-scale wind-tunnel testing or actual prototype evaluation, with only one example identified as having been tested on a production helicopter. In addition, a comparative Technology Readiness Level (TRL) assessment is presented for both rotary-wing and fixed-wing morphing actuation systems, enabling a structured evaluation of relative technology maturity, experimental validation depth, and proximity to operational implementation. Building upon this assessment, a morphing Actuation Concept-Transfer Feasibility (ACTF) study is also provided, examining the potential for adapting mature fixed-wing morphing actuation technologies for application in rotary-wing environments, while identifying the key structural, aerodynamic, and operational constraints that currently limit direct technology transfer. This study addresses and proposes opportunities for a novel rotary actuation system design and concludes by suggesting the potential for future research on more effectual systems to include full-chord configuration over larger spanwise blade footprints with innovative actuation mechanisms that could be utilised and progressed through all development stages from numerical studies to full-scale fabrication. Full article
(This article belongs to the Section Aeronautics)
►▼ Show Figures

Figure 1

35 pages, 6392 KB  
Article
EO-MADDPG: An Improved Reinforcement Learning Approach for Multi-UAV Pursuit–Evasion Games
by Xiao Wang, Mengyu Wang, Xueqian Bai, Zhe Ma, Kewu Sun and Jiake Li
Aerospace 2026, 13(3), 296; https://doi.org/10.3390/aerospace13030296 - 21 Mar 2026
Viewed by 262
Abstract
To advance research in multi-agent reinforcement learning (MARL) for pursuit–evasion scenarios, this paper introduces a novel algorithm called Expert Knowledge and Opponent Modeling Multi-UAV Deep Deterministic Policy Gradient (EO-MADDPG). EO-MADDPG consists of two key components: the integration of expert knowledge and real-time sampled [...] Read more.
To advance research in multi-agent reinforcement learning (MARL) for pursuit–evasion scenarios, this paper introduces a novel algorithm called Expert Knowledge and Opponent Modeling Multi-UAV Deep Deterministic Policy Gradient (EO-MADDPG). EO-MADDPG consists of two key components: the integration of expert knowledge and real-time sampled data and the prediction of evader UAV actions. The expert knowledge includes a multi-UAV formation control algorithm and an encirclement strategy, which incorporates consensus algorithms and Apollonius circle guidance. Additionally, the network-training framework is optimized by integrating information about opponent actions under a fixed policy for improved prediction accuracy. The experiments focus on three vs. one and three vs. two scenarios, where pursuer UAVs utilize EO-MADDPG and evader UAVs follow fixed policies with Gaussian perturbations. Experimental results show that EO-MADDPG achieves success rates of 99.9 ± 0.3% and 97.5 ± 1.4% (mean ± std over five seeds) in three vs. one and three vs. two pursuit–evasion simulations, respectively, outperforming the baseline MADDPG (72.7 ± 6.0% and 64.4 ± 34.4%). Ablation studies and cooperative landmark tasks further demonstrate improved training stability and interpretability. Full article
(This article belongs to the Section Aeronautics)
►▼ Show Figures

Figure 1

25 pages, 2444 KB  
Article
User Evaluation by Remote Pilots of Two Types of Detect-and-Avoid Systems: Remain Well Clear Bands Versus Route Guidance
by Sybert Stroeve, Ana Tanevska, Mirco Kroon and Ginevra Castellano
Aerospace 2026, 13(3), 295; https://doi.org/10.3390/aerospace13030295 - 20 Mar 2026
Viewed by 296
Abstract
The remain well clear (RWC) function of a detect-and-avoid (DAA) system provides guidance to a remote pilot (RP) of a remotely piloted aircraft to prevent a conflict from developing into a collision hazard. The ACAS Xu standard is a decision support system that [...] Read more.
The remain well clear (RWC) function of a detect-and-avoid (DAA) system provides guidance to a remote pilot (RP) of a remotely piloted aircraft to prevent a conflict from developing into a collision hazard. The ACAS Xu standard is a decision support system that uses RWC bands to advise a RP which headings to avoid. A recent A* DAA system is a resolution support system that advises a RP which route to take. The objective of this study is to achieve structured feedback by professional RPs on the horizontal RWC guidance of both systems. Nine RPs participated in on-line experiments, where they were shown videos of DAA displays of encounter scenarios between two aircraft. At various stages the RPs were asked for their opinion about transparency, pilot manoeuvring, situation awareness, display orientation, risk perception, competence, trust, and overall system preference. The results show that the scores for competence, trust and pilot manoeuvring were significantly higher, and the score for perceived risk was significant lower for the RWC route guidance. Overall, 89% of the RPs preferred the RWC route guidance, while one RP had no preference. An implication of the uncertainty in pilot behaviour is that ACAS Xu model-based optimisation may provide suboptimal RWC guidance strategies, while the A* DAA optimisation can be managed effectively. Full article
(This article belongs to the Section Air Traffic and Transportation)
►▼ Show Figures

Figure 1

15 pages, 21867 KB  
Article
Enabling Scalable and Efficient Low-Altitude Airspace Utilization for Dense Urban Operations
by Yamin Zhang, Rong Xu, Bin Hu, Kaiyu Nie, Hang Zhao, Bo Chen and Qinglei Kong
Aerospace 2026, 13(3), 294; https://doi.org/10.3390/aerospace13030294 - 20 Mar 2026
Viewed by 312
Abstract
The rapid growth of low-altitude air traffic demands airspace evaluation frameworks that are scalable, flexible, and efficient. However, existing airspace partitioning strategies, primarily designed for sparse, long-distance civil aviation, are ill-suited to the dense and complex low-altitude environment. Moreover, the heterogeneous nature of [...] Read more.
The rapid growth of low-altitude air traffic demands airspace evaluation frameworks that are scalable, flexible, and efficient. However, existing airspace partitioning strategies, primarily designed for sparse, long-distance civil aviation, are ill-suited to the dense and complex low-altitude environment. Moreover, the heterogeneous nature of low-altitude conditions cannot be adequately captured. To address this challenge, we propose a novel low-altitude airspace evaluation framework centered on a hierarchical voxel-based partitioning strategy. This strategy explicitly accommodates the diverse operational requirements of drones across different airspace layers. We couple this with an efficient multi-resolution airspace unit encoding mechanism that dynamically aggregates and evaluates airspace availability. To demonstrate the practical utility of our framework, we further develop an energy-aware, multi-scale route-planning algorithm that operates seamlessly across the hierarchical representation. Simulation results show that our method significantly improves computational efficiency in airspace evaluation, while the proposed planner achieves higher energy efficiency compared to conventional approaches like A*. Full article
(This article belongs to the Section Air Traffic and Transportation)
►▼ Show Figures

Figure 1

20 pages, 2607 KB  
Article
A Data-Driven Methodology for Developing a Future Design Day Flight Schedule (DDFS)
by Eunji Kim, Seokjae Yun and Hojong Baik
Aerospace 2026, 13(3), 293; https://doi.org/10.3390/aerospace13030293 - 19 Mar 2026
Viewed by 189
Abstract
The design day flight schedule (DDFS) plays a pivotal role in airport simulation and infrastructure planning. Despite its importance, previous studies and global guidelines offer only broad recommendations for DDFS preparation, lacking detailed methodologies and empirical validation. This study proposes a systematic, data-driven [...] Read more.
The design day flight schedule (DDFS) plays a pivotal role in airport simulation and infrastructure planning. Despite its importance, previous studies and global guidelines offer only broad recommendations for DDFS preparation, lacking detailed methodologies and empirical validation. This study proposes a systematic, data-driven approach for generating a future DDFS that accounts for projected demand, airline behavior, and regional traffic characteristics. Leveraging historical flight operation data and probabilistic distributions, the proposed method captures existing patterns and anticipated market changes comprehensively. To realistically define each flight’s operational characteristics, a structured 10-step procedure is employed to generate and assign attributes—such as aircraft type, origin/destination airport, and turnaround time—based on empirical patterns and logical constraints. The proposed approach is applied to Incheon International Airport as a case study, demonstrating its practical utility and scalability. The generated DDFSs are shown to be consistent with target-year forecasts in terms of peak-hour operations and fleet composition, with deviations remaining within a small error range. Additional validation confirms that key operational characteristics, including airline shares, connection patterns, and turnaround times, are reproduced with acceptable accuracy. By bridging the gap between high-level guidance and implementable practice, this study contributes a replicable framework for future DDFS generation and provides actionable insights for airport planners aiming to better anticipate operational demands. Full article
(This article belongs to the Special Issue Next-Generation Airport Operations and Management)
►▼ Show Figures

Figure 1

22 pages, 37782 KB  
Article
Fast Data-Driven Noise Prediction for an Aircraft in Unconventional Configuration Using Flight Test Data
by Dominik Eisenhut and Andreas Strohmayer
Aerospace 2026, 13(3), 292; https://doi.org/10.3390/aerospace13030292 - 19 Mar 2026
Viewed by 278
Abstract
New, highly integrated, disruptive aircraft concepts are being devised to reduce aviation’s environmental footprint, but their performance is oftentimes challenging for the aircraft designer to assess. Furthermore, these novel aircraft often introduce new risks, such as noise, that cannot be addressed quickly by [...] Read more.
New, highly integrated, disruptive aircraft concepts are being devised to reduce aviation’s environmental footprint, but their performance is oftentimes challenging for the aircraft designer to assess. Furthermore, these novel aircraft often introduce new risks, such as noise, that cannot be addressed quickly by available methods. Overall, in the pursuit of more environmental friendly aircraft configurations and the lack of methods to design such aircraft, aircraft-level trade-offs between noise and performance are challenging. The present study aims to close this gap by using a machine learning-based approach for one unconventional aircraft to investigate usability in the early stages of aircraft design. Based on overflight noise measurements, noise models for this aircraft are created with different approaches and base models. The single-output models show good performance, with mean absolute errors around 1 dB, good rank correlations and R2 scores above 0.9. Support vector regression provides reasonably good agreement from experiments requiring only a small effort to set up; Neural Networks achieve better performance, but increased effort is required to obtain the model. Full article
(This article belongs to the Special Issue 15th EASN International Conference on Innovation in Aviation & Space Towards Sustainability Today and Tomorrow)
►▼ Show Figures

Figure 1

27 pages, 14575 KB  
Article
An Ultra-High-Aspect-Ratio Telescopic Continuum Robot Design for Aero-Engine Borescope Inspection
by Da Hong, Yuancan Huang, Nianfeng Shao, Yiming Wang and Weiheng Zhong
Aerospace 2026, 13(3), 291; https://doi.org/10.3390/aerospace13030291 - 19 Mar 2026
Viewed by 378
Abstract
Conventional borescopes are limited by inadequate mechanical flexibility, poor environmental adaptability and reachability, and heavy reliance on operator expertise during aero-engine inspections, making it difficult to meet the demands for efficient and dependable in situ nondestructive evaluation (NDE). This paper presents a novel [...] Read more.
Conventional borescopes are limited by inadequate mechanical flexibility, poor environmental adaptability and reachability, and heavy reliance on operator expertise during aero-engine inspections, making it difficult to meet the demands for efficient and dependable in situ nondestructive evaluation (NDE). This paper presents a novel telescopic continuum robot mechanism with an ultra-high aspect ratio (63.75:1) and three constant-curvature segments, achieving a synergistic design between the robot’s body structure and the long-stroke linear actuator of its central backbone to realize ultra-high-aspect-ratio configurations. This design improves the robot’s ability to access complex and confined internal spaces within aero-engines, thereby reducing inspection blind spots. Furthermore, a configuration-space control strategy integrating kinematic decoupling and driving tendon tension compensation is proposed. This strategy addresses the issues of multi-segment actuation coupling and tendon slack, ensuring the motion control performance for in situ aero-engine blade inspection. The feasibility of the mechanism design was validated through an experimental simulation platform incorporating both turbine blade and compressor blade scenarios. This work offers a new solution for in situ NDE in aero-engines by synergistically integrating an innovative ultra-high-aspect-ratio telescopic mechanism with a dedicated configuration-space controller that addresses multi-segment coupling and tendon slack. Full article
(This article belongs to the Section Aeronautics)
►▼ Show Figures

Figure 1

28 pages, 7242 KB  
Article
State of Health Prediction Method for the Gas Turbine Aero-Engine Fuel Metering Units Based on Inverted Stabilized LSTM-Transformer
by Yingzhi Huang, Xiaonan Wu, Junwei Li and Linfeng Gou
Aerospace 2026, 13(3), 290; https://doi.org/10.3390/aerospace13030290 - 19 Mar 2026
Viewed by 183
Abstract
As a critical actuator in aero-engine control systems, the health condition of the Fuel Metering Unit (FMU) directly influences flight safety and maintenance efficiency, making the precise prediction of its degradation process a core task in the engine’s Prognostic and Health Management (PHM). [...] Read more.
As a critical actuator in aero-engine control systems, the health condition of the Fuel Metering Unit (FMU) directly influences flight safety and maintenance efficiency, making the precise prediction of its degradation process a core task in the engine’s Prognostic and Health Management (PHM). This paper presents a novel inverted stabilized LSTM-Transformer (isLTransformer) approach for predicting the health state of aero-engine FMUs, addressing the limitations of existing methods in modeling long-sequence multivariate data. Firstly, a Composite Health Indicator (CHI) is constructed through semi-supervised learning (SSL), which fuses multi-sensor monitoring data to quantitatively characterize the degradation trend of the FMU throughout its operational lifecycle. Secondly, the proposed isLTransformer model is designed by replacing the feedforward network in traditional iTransformer with a stabilized LSTM module, which maintains the self-attention mechanism’s capability to explicitly model dynamic correlations between multiple variables while enhancing the ability to capture nonlinear degradation within individual variables. A physical FMU test bench is designed for the real-world PHM degradation experiments, and the collected dataset was used to demonstrate the effectiveness of the proposed method. Evaluation metrics, including Root Mean Square Error (RMSE) and Mean Absolute Error (MAE), are employed to assess the prediction accuracy. The proposed method demonstrates high monotonicity and trend consistency in CHI construction. Compared to the inverted Transformer (iTransformer) and iTransformer- Bi-directional Long Short-Term Memory (BiLSTM), the proposed isLTransformer framework demonstrates significantly reduced prediction errors, validating its superiority in multivariate long-sequence prediction tasks and effectiveness for aero-engine FMU health prediction. Full article
(This article belongs to the Section Aeronautics)
►▼ Show Figures

Figure 1

23 pages, 4349 KB  
Article
A Next-Generation Hybrid Approach for Data-Driven Fuel-Efficient Flight Control of Commercial Aircraft
by Ukbe Üsame Ucar, Zülfü Kuzu and Hakan Aygün
Aerospace 2026, 13(3), 289; https://doi.org/10.3390/aerospace13030289 - 19 Mar 2026
Viewed by 237
Abstract
In this study, a novel hybrid optimization approach is proposed to minimize the fuel consumption of commercial aircraft by taking flight-related and meteorological constraints into account during the cruise phase. The new method, the Decision Tree–Robust Multiple Regression–Harris Hawks Optimization Algorithm (DRHA), incorporates [...] Read more.
In this study, a novel hybrid optimization approach is proposed to minimize the fuel consumption of commercial aircraft by taking flight-related and meteorological constraints into account during the cruise phase. The new method, the Decision Tree–Robust Multiple Regression–Harris Hawks Optimization Algorithm (DRHA), incorporates data segmentation based on decision trees, modeling of robust multiple regression, and the Harris Hawks optimization algorithm. In this context, a PID speed controller for a Boeing 737-800 aircraft was developed by employing a Software-in-the-Loop (SIL) framework that establishes real-time data exchange between MATLAB/Simulink and the FAA-approved X-Plane flight simulator. Within this framework, a simulation-based fuel consumption dataset was obtained from 1032 different scenarios encompassing various combinations of altitude, speed, aircraft weight, wind speed, and wind direction, thus aiming to reflect a wide range of realistic flight operating conditions. According to comparative analysis outcomes, the proposed DRHA approach significantly outperformed conventional statistical and machine learning-based methods in modeling fuel consumption equations. Namely, a mean absolute error (MAE) and R2 value are achieved with values of 1.24 and 0.90, respectively. Moreover, PID controller parameters are optimized under varying conditions thanks to the DRHA method, yielding between 0.07% and 5.33% fuel savings compared to manually tuned controllers. Tests performed under different altitudes, aircraft weights, and wind conditions confirm the algorithm’s robustness and adaptability. The proposed method is anticipated to offer scalable and adaptable solutions for various types of aircraft and real-time control systems. Full article
(This article belongs to the Section Aeronautics)
►▼ Show Figures

Figure 1

16 pages, 3521 KB  
Article
Shape Optimization of Aircraft Outflow Valve for Maximum Thrust Recovery
by Tasos Karageorgiou, Pela Katsapoxaki, Michael Moeller and El Hassan Ridouane
Aerospace 2026, 13(3), 288; https://doi.org/10.3390/aerospace13030288 - 18 Mar 2026
Viewed by 211
Abstract
The present study demonstrates a step-by-step method for optimizing the outflow valve geometry and maximizing thrust generation. In this system, the skin-mounted OutFlow Valve (OFV) acts as a convergent–divergent nozzle and, as such, the De Laval nozzle equations are considered as guidance for [...] Read more.
The present study demonstrates a step-by-step method for optimizing the outflow valve geometry and maximizing thrust generation. In this system, the skin-mounted OutFlow Valve (OFV) acts as a convergent–divergent nozzle and, as such, the De Laval nozzle equations are considered as guidance for the shape optimization. The performance of the skin-mounted flapped OFV optimized designs is assessed with a combination of analytical equations and Computational Fluid Dynamics (CFD) methods. The three-dimensional Reynolds-Averaged Navier–Stokes (RANS) yield reliable thrust recovery estimates and reveal key aspects of the aerodynamic flow behaviour through the valve, highlighting the interaction between the skin-mounted flapped OFV components. The results compare well with the analytical approach, providing a basis upon which a skin-mounted flapped OFV can be tailored for a specific mission. Full article
(This article belongs to the Special Issue 15th EASN International Conference on Innovation in Aviation & Space Towards Sustainability Today and Tomorrow)
►▼ Show Figures

Figure 1

28 pages, 2467 KB  
Review
Light-Curve Classification of Resident Space Objects for Space Situational Awareness: A Scoping Review
by Minyoung Hwang, Vithurshan Suthakar, Randa Qashoa, Regina S. K. Lee and Gunho Sohn
Aerospace 2026, 13(3), 287; https://doi.org/10.3390/aerospace13030287 - 18 Mar 2026
Viewed by 369
Abstract
The proliferation of Resident Space Objects (RSOs), including satellites, rocket bodies, and debris, poses escalating challenges for Space Situational Awareness (SSA). Optical light curves capture temporal brightness variations influenced by factors such as attitude variation, viewing geometry, and surface properties. When appropriately processed [...] Read more.
The proliferation of Resident Space Objects (RSOs), including satellites, rocket bodies, and debris, poses escalating challenges for Space Situational Awareness (SSA). Optical light curves capture temporal brightness variations influenced by factors such as attitude variation, viewing geometry, and surface properties. When appropriately processed and analyzed, these data can support RSO characterization and classification. This paper presents a scoping review of machine learning (ML) and deep learning (DL) methods for RSO classification using light-curve data. From 297 peer-reviewed studies published between 2014 and 2025, a screened subset of 29 works is selected for detailed methodological comparison. We trace the methodological evolution from handcrafted feature engineering toward convolutional, recurrent, and self-supervised models that learn representations directly from photometric time series. An analysis of three publicly accessible databases, Mini Mega TORTORA, Space Debris Light-Curve Database, and Ukrainian Database, reveals pronounced class imbalance, with payloads comprising over 80% of observations. While models trained on simulated data routinely achieve 95 to 99% accuracy, performance on measured light curves degrades to 75 to 92%, exposing a persistent gap between simulation and observation. We further identify data scarcity, repeated observations of the same objects, and inconsistent evaluation protocols as key barriers to reproducible benchmarking. Future progress will require benchmark-ready, sensor-aware datasets spanning diverse orbital regimes and viewing geometries, alongside physics-informed and transfer-learning approaches that improve robustness across sensors and between synthetic and observational domains. Full article
(This article belongs to the Special Issue Advances in Space Surveillance and Tracking)
►▼ Show Figures

Figure 1

25 pages, 2898 KB  
Article
A Multi-Fidelity Aeroelastic Toolchain: From UAVs to Hydrogen Transport Aircraft
by Fanglin Yu, Carlos Sebastia Saez and Mirko Hornung
Aerospace 2026, 13(3), 286; https://doi.org/10.3390/aerospace13030286 - 18 Mar 2026
Viewed by 225
Abstract
The increasing adoption of high-aspect-ratio wings to improve aerodynamic efficiency introduces significant structural flexibility, necessitating the integration of aeroelastic considerations into the earliest design stages. While critical, existing frameworks often lack the multi-fidelity modeling capabilities and automated workflows required to bridge conceptual design [...] Read more.
The increasing adoption of high-aspect-ratio wings to improve aerodynamic efficiency introduces significant structural flexibility, necessitating the integration of aeroelastic considerations into the earliest design stages. While critical, existing frameworks often lack the multi-fidelity modeling capabilities and automated workflows required to bridge conceptual design and high-fidelity verification. This paper presents the Flexible Aero-Structural Toolbox (FAST), a modular framework supporting both beam and shell structural modeling and integrated with MSC NASTRAN for industry-standard aeroelastic simulation. The toolbox’s capabilities are demonstrated through modal, flutter, and static aeroelastic analyses across three distinct configurations: the P-FLEX UAV, the Ventus sailplane, and an A320-like transport aircraft, including its hydrogen-powered derivative. Results show that FAST accurately captures the aeroelastic characteristics of high-aspect-ratio wings and effectively predicts loads for large-scale flexible airframes. Notably, analysis of the hydrogen configuration reveals a significant 25% increase in wing bending moments for the “dry” wing condition compared to standard kerosene configurations. Furthermore, the tool’s ability to model unconventional mass distributions, such as cryogenic fuel tanks, highlights its adaptability for disruptive aircraft technologies. The study concludes that FAST provides a versatile, physics-based decision-making environment that significantly improves efficiency in the aeroelastic analysis process without compromising simulation fidelity. Full article
(This article belongs to the Special Issue 15th EASN International Conference on Innovation in Aviation & Space Towards Sustainability Today and Tomorrow)
►▼ Show Figures

Figure 1

19 pages, 1361 KB  
Article
A New Method for Optimizing Low-Earth-Orbit Satellite Communication Links Based on Deep Reinforcement Learning
by He Yu, Shengli Li, Junchao Wu, Yanhong Sun and Limin Wang
Aerospace 2026, 13(3), 285; https://doi.org/10.3390/aerospace13030285 - 18 Mar 2026
Viewed by 248
Abstract
In low-Earth-orbit (LEO) satellite networks, the need for intelligent parameter-adjustment strategies has become increasingly critical due to the presence of highly dynamic channel conditions, limited spectrum resources, and complex interference environments. In this paper, a method for optimizing LEO satellite communication links based [...] Read more.
In low-Earth-orbit (LEO) satellite networks, the need for intelligent parameter-adjustment strategies has become increasingly critical due to the presence of highly dynamic channel conditions, limited spectrum resources, and complex interference environments. In this paper, a method for optimizing LEO satellite communication links based on deep reinforcement learning (DRL) is proposed. Through the optimization of the transmit power, the modulation and coding scheme (MCS), the beamforming parameters, and the retransmission mechanisms, adaptive link control is achieved in dynamic operational scenarios. A multidimensional state space is constructed, within which the channel state information, the interference environment, and the historical performance metrics are integrated. The spatio-temporal characteristics of the channel are extracted by means of a hybrid neural architecture that incorporates a convolutional neural network (CNN) and a long short-term memory (LSTM) network. To effectively accommodate both continuous and discrete action spaces, a hybrid DRL framework that combines proximal policy optimization (PPO) with a deep Q-network (DQN) is employed, thereby enabling cross-layer optimization of the physical-layer and link-layer parameters. The results demonstrate that substantial improvements in throughput, bit error rate (BER), and transmit-power efficiency are achieved under severely time-varying channel conditions, which provides a new idea for resource management and dynamic-environment adaptation in satellite communication systems. Full article
(This article belongs to the Special Issue Advanced Spacecraft/Satellite Technologies (2nd Edition))
►▼ Show Figures

Figure 1

27 pages, 8384 KB  
Article
A Simulation and TOPSIS Approach to the Satellite Constellation Design Problem
by Mikkel Søby Kramer, Frederik Christensen, Veronica Hjort, Peter Nielsen and Alex Elkjær Vasegaard
Aerospace 2026, 13(3), 284; https://doi.org/10.3390/aerospace13030284 - 18 Mar 2026
Viewed by 294
Abstract
The design of satellite constellations is a complex optimization problem interdependent with other decision problems and multiple competing, user-specific criteria. Consequently, it is very difficult to make a final decision on the constellation design. This study proposes a full simulation and evaluation framework [...] Read more.
The design of satellite constellations is a complex optimization problem interdependent with other decision problems and multiple competing, user-specific criteria. Consequently, it is very difficult to make a final decision on the constellation design. This study proposes a full simulation and evaluation framework for designing a satellite constellation. Firstly, constructing a solution space by constraining orbital parameters and varying satellite count and plane configuration. Secondly, employing six evaluation metrics—covering both cost and coverage—that are weighted via the case company, Sternula’s setting, with the TOPSIS approach for ranking the candidate constellations. A subsequent sensitivity analysis evaluates robustness to shifts in criterion weights and per-satellite cost. The study indicates that a Walker Star constellation with 97.5° inclination, 105 satellites in 15 planes (phasing 7) achieves the best cost–coverage balance for the case company and remains stable under weight and cost variations. Full article
(This article belongs to the Special Issue Decision-Making Strategies for Aerospace Mission Design and Planning)
►▼ Show Figures

Graphical abstract

25 pages, 2445 KB  
Article
Reentry Trajectory Optimization of Hypersonic Vehicle Based on Multi-Strategy Improved WOA Optimized Attention-LSTM Network
by Encheng Dai, Guangbin Cai, Yonghua Fan, Hui Xu, Hao Wei and Xin Li
Aerospace 2026, 13(3), 283; https://doi.org/10.3390/aerospace13030283 - 17 Mar 2026
Viewed by 290
Abstract
Trajectory optimization of hypersonic vehicles face challenges from complex aerodynamic environments and multiple constraints, where traditional offline optimization methods struggle to meet real-time requirements. This study proposes a novel online trajectory optimization framework for hypersonic vehicles that integrates a multi-strategy improved whale optimization [...] Read more.
Trajectory optimization of hypersonic vehicles face challenges from complex aerodynamic environments and multiple constraints, where traditional offline optimization methods struggle to meet real-time requirements. This study proposes a novel online trajectory optimization framework for hypersonic vehicles that integrates a multi-strategy improved whale optimization algorithm (MWOA) with an attention-mechanism Long Short-Term Memory (AM-LSTM) network. First, an offline trajectory dataset under aerodynamic uncertainties is generated using sequential second-order cone programming (SOCP). Subsequently, a multi-head attention mechanism is incorporated into the LSTM network to effectively capture sequential dependencies within the trajectory data. To automate the hyperparameter tuning of the AM-LSTM architecture, a multi-strategy improved whale optimization algorithm is developed, which incorporates circle chaotic mapping for population initialization, a nonlinear convergence factor to balance global and local search, and a dynamic golden-sine mutation strategy to enhance optimization robustness. The trained MWOA-AM-LSTM hybrid model is then employed for real-time trajectory generation. Numerical simulation results demonstrate that the proposed framework achieves superior terminal accuracy under aerodynamic perturbations, validating its effectiveness and robustness for hypersonic vehicle reentry trajectory optimization. Full article
(This article belongs to the Section Aeronautics)
►▼ Show Figures

Figure 1

24 pages, 2763 KB  
Article
Dynamic Hierarchical Fusion for Space Multi-Target Passive Tracking with Limited Field-of-View
by Jizhe Wang, Di Zhou, Runle Du and Jiaqi Liu
Aerospace 2026, 13(3), 282; https://doi.org/10.3390/aerospace13030282 - 17 Mar 2026
Viewed by 205
Abstract
Space-based multi-target passive tracking is critical for space situational awareness, but faces severe challenges due to the limited field-of-view (FoV) and directional ambiguity of onboard sensors. These constraints often lead to target loss, poor observability, and decreased estimation accuracy. To address these issues, [...] Read more.
Space-based multi-target passive tracking is critical for space situational awareness, but faces severe challenges due to the limited field-of-view (FoV) and directional ambiguity of onboard sensors. These constraints often lead to target loss, poor observability, and decreased estimation accuracy. To address these issues, different fusion architectures have been explored. While centralized measurement-level fusion offers superior accuracy for estimating target states, distributed estimation-level fusion provides greater reliability for estimating the number of targets. To adaptively leverage these two complementary strengths, a dynamic hierarchical fusion method through real-time optimization of the fusion topology is proposed. Specifically, at each decision epoch, sensor nodes are dynamically partitioned into local fusion nodes (LFNs) and detection-only nodes (DONs). Each LFN receives measurements from selected DONs and executes an iterated-correction Gaussian-mixture probability hypothesis density filter. Subsequently, LFNs share and fuse their estimates using the intensity-dependent arithmetic average fusion. This dynamic process is achieved by applying a sensor management scheme based on partially observable Markov decision process (POMDP). To ensure accurate cardinality estimation, the reward function in POMDP utilizes the posterior expected number of targets. The resultant optimization is efficiently solved using a binary particle swarm optimization algorithm. Numerical and hardware-in-the-loop simulations demonstrate the effectiveness of the proposed method in balancing the accuracy of target number and state estimation. Full article
(This article belongs to the Section Astronautics & Space Science)
►▼ Show Figures

Figure 1

23 pages, 4280 KB  
Article
Data-Driven Reduced-Order Modeling for Aeroelastic Load Prediction of Rotor Blades
by Nan Luo, Zhihao Yu and Weidong Yang
Aerospace 2026, 13(3), 281; https://doi.org/10.3390/aerospace13030281 - 17 Mar 2026
Viewed by 263
Abstract
This paper proposes a data-driven model for predicting rotor fluid-structure interaction (FSI) load with efficient aeroelastic analysis. Unsteady flow-field snapshots obtained from computational fluid dynamics (CFD) simulations are first processed using Proper Orthogonal Decomposition (POD) to reduce the dimensionality of the flow data [...] Read more.
This paper proposes a data-driven model for predicting rotor fluid-structure interaction (FSI) load with efficient aeroelastic analysis. Unsteady flow-field snapshots obtained from computational fluid dynamics (CFD) simulations are first processed using Proper Orthogonal Decomposition (POD) to reduce the dimensionality of the flow data and extract the dominant modal time coefficients. Based on these reduced-order representations, the Dynamic Mode Decomposition with control (DMDc) method is used to identify a time-domain state-space model of the aerodynamic system. The identified data-driven aerodynamic model is coupled with the structural dynamic equations, which allows time-domain reconstruction and prediction of unsteady aerodynamic forces and structural loads under aeroelastic interactions. Hence, an efficient reduced-order model for aerodynamic load is established. The proposed approach is first validated using a two-dimensional airfoil subjected to different motion inputs, where the reduced-order aerodynamic predictions are compared with high-fidelity CFD results. Then, a three-dimensional sectional reduced-order model for a rotor is developed based on blade element theory, and aeroelastic coupled simulations are conducted for the SA349 rotor. The results demonstrate that the proposed method can accurately capture unsteady aerodynamic loads and aeroelastic responses, while significantly improving computational efficiency compared to high-fidelity simulations. Full article
(This article belongs to the Section Aeronautics)
►▼ Show Figures

Figure 1

19 pages, 6023 KB  
Article
Conceptual Study of a Manned European Martian Rotorcraft for Passenger and Cargo Transport in Future Mars Missions
by Jakub Kocjan, Robert Rogólski, Stanisław Kachel and Łukasz Kiszkowiak
Aerospace 2026, 13(3), 280; https://doi.org/10.3390/aerospace13030280 - 17 Mar 2026
Viewed by 302
Abstract
This work presents a space-oriented extension of an existing research program focused on developing innovative approaches and design solutions for rotorcraft. The study builds upon recent research conducted at the Military University of Technology, where new methods for main rotor optimization using parametric [...] Read more.
This work presents a space-oriented extension of an existing research program focused on developing innovative approaches and design solutions for rotorcraft. The study builds upon recent research conducted at the Military University of Technology, where new methods for main rotor optimization using parametric modeling were developed. The primary objective of this research is to investigate the feasibility of designing a rotorcraft capable of operating in the Martian environment. The proposed vehicle is intended to perform vertical takeoff, flight, and landing; sustain at least two hours of continuous operation; and transport a pilot with either a passenger or an equivalent payload of 100 kg. Additionally, the rotorcraft should be capable of being restored to an airworthy condition after each mission and prepared for reuse while maintaining its operational capabilities. Preliminary performance analyses were conducted based on Martian atmospheric conditions. Analytical models implemented in dedicated computational tools were used to estimate rotor dimensions, performance, and trim requirements. Several rotor configurations were evaluated to assess the feasibility of manned flight with an additional payload under extraterrestrial conditions. The results identify key limitations, risks, and technological challenges, while also highlighting potential design opportunities. The study culminates in a conceptual design proposal for a future Martian rotorcraft mission. The findings demonstrate the applicability of the proposed methodology and provide a foundation for further research and development in planetary rotorcraft systems. Full article
(This article belongs to the Special Issue 15th EASN International Conference on Innovation in Aviation & Space Towards Sustainability Today and Tomorrow)
►▼ Show Figures

Figure 1

27 pages, 4763 KB  
Article
Orbit-Prior-Guided Target-Centered Stacking for Space Surveillance and Tracking Under Dynamic-Platform Optical Observations
by Lanze Qu, Junchi Liu, Hongwen Li, Zhiyong Wu, Jianli Wang and Kainan Yao
Aerospace 2026, 13(3), 279; https://doi.org/10.3390/aerospace13030279 - 17 Mar 2026
Viewed by 272
Abstract
In visible-light optical observations for Space Surveillance and Tracking (SST) from ground-based dynamic platforms, attitude disturbances and field-of-view discontinuities frequently undermine interframe geometric consistency, leading to energy diffusion and unstable gain in multi-frame stacking for faint space objects. We propose orbit-prior- guided target-centered [...] Read more.
In visible-light optical observations for Space Surveillance and Tracking (SST) from ground-based dynamic platforms, attitude disturbances and field-of-view discontinuities frequently undermine interframe geometric consistency, leading to energy diffusion and unstable gain in multi-frame stacking for faint space objects. We propose orbit-prior- guided target-centered stacking (OPG-TCS), a tracking-oriented post-processing method designed to stabilize target energy accumulation and improve enhancement reliability under dynamic observation conditions. OPG-TCS performs frame-wise astrometric calibration using star fields (WCS) and leverages projected orbit priors to predict target pixel locations, enabling local cropping and target-centered alignment/stacking without relying on full-frame geometric consistency. We evaluate OPG-TCS on multiple real-world dynamic-platform sequences and compare it with direct stacking and representative robust baselines. Signal-to-noise ratio (SNR) is used as the primary metric, while auxiliary indicators of peak prominence, energy concentration, and shape consistency are employed to assess robustness across varying stacking depths. The results show that OPG-TCS provides stable enhancement over different frame counts; in representative 50-frame fusions, its relative SNR surpasses direct stacking by 33.7–97.8%. These findings suggest that OPG-TCS offers a practical and robust enhancement strategy for SST-oriented observation of faint space objects, supporting more reliable detection and subsequent tracking analysis. Full article
(This article belongs to the Special Issue Advances in Space Surveillance and Tracking)
►▼ Show Figures

Figure 1

22 pages, 5574 KB  
Article
Thermo-Mechanical Design of the C/C-SiC-Based Thermal Protection Structure for the Forebody of the Hypersonic Sounding Rocket STORT
by Giuseppe Daniele Di Martino, Thomas Reimer, Luis Baier, Lucas Dauth, Dorian Hargarten and Ali Gülhan
Aerospace 2026, 13(3), 278; https://doi.org/10.3390/aerospace13030278 - 16 Mar 2026
Viewed by 379
Abstract
Re-entry flights of reusable first or upper stages typically foresee phases in the hypersonic flight regime, characterized by severe aero-thermal loads which could become critical for the most exposed components, like the vehicle forebody or the fin leading edges. These require consequently dedicated [...] Read more.
Re-entry flights of reusable first or upper stages typically foresee phases in the hypersonic flight regime, characterized by severe aero-thermal loads which could become critical for the most exposed components, like the vehicle forebody or the fin leading edges. These require consequently dedicated thermal protection systems (TPS), whose design generally requires a multi-disciplinary approach. In this framework, a viable solution is the use of high-temperature resistant ceramic matrix composite (CMC) structures, but the implementation of such technology, especially for the manufacturing of complex components and its application in real flight conditions, still presents significant challenges. In this work, the design activities for the CMC-based TPS of the payload forebody of a hypersonic sounding rocket are presented, developed within the framework of the STORT project, whose mission includes in flight demonstration of multiple critical technologies required for sustained flight at Mach numbers above 8, corresponding to a significantly high integral thermal load. Full article
(This article belongs to the Section Aeronautics)
►▼ Show Figures

Figure 1

20 pages, 1680 KB  
Article
Efficient Inference of Neural Networks with Cooperative Integer-Only Arithmetic on a SoC FPGA for Onboard LEO Satellite Network Routing
by Bogeun Jo, Heoncheol Lee, Bongsoo Roh and Myonghun Han
Aerospace 2026, 13(3), 277; https://doi.org/10.3390/aerospace13030277 - 16 Mar 2026
Viewed by 236
Abstract
Low Earth orbit (LEO) satellite networks require real-time routing to cope with dynamic topology variations caused by continuous orbital motion. As an alternative to conventional routing approaches, deep reinforcement learning (DRL) has recently gained attention as an effective means for optimizing routing paths. [...] Read more.
Low Earth orbit (LEO) satellite networks require real-time routing to cope with dynamic topology variations caused by continuous orbital motion. As an alternative to conventional routing approaches, deep reinforcement learning (DRL) has recently gained attention as an effective means for optimizing routing paths. To solve routing problems modeled as a grid-based Markov decision process (grid-based MDP), DRL methods such as CNN-based Dueling DQN have been proposed. However, these approaches are difficult to implement in practice. In particular, the substantial floating-point computation and memory traffic of CNN inference make real-time onboard inference challenging under the stringent power and resource constraints of satellite platforms. To address these constraints, this paper proposes an INT8 quantization and hardware–software co-design framework using heterogeneous SoC FPGA acceleration. We offload compute-intensive CNN inference to the programmable logic (PL), while the processing system (PS) orchestrates overall control and data movement, forming a collaborative PS–PL architecture. Furthermore, we integrate the NITI-style two-pass scaling with PS–PL exponent propagation to preserve end-to-end integer consistency without floating-point conversion. To demonstrate its practical onboard feasibility, we employ standard accelerator implementation choices—such as output-stationary scheduling and on-chip prefetching—and conduct an ablation study over independently tunable axes (PE array size and PS-side buffer reuse) to quantify their incremental contributions. Experimental results show that the proposed PS–PL cooperative scheme dramatically reduces computation time compared to a PS-only reference implementation on the same platform. Full article
(This article belongs to the Section Astronautics & Space Science)
►▼ Show Figures

Figure 1

29 pages, 14085 KB  
Article
Dynamic Trajectory Planning for Autonomous Parafoil Homing Under Wind Disturbances
by Luqi Yan, Yanguo Song, Huanjin Wang, Zhiwei Shi and Yilei Song
Aerospace 2026, 13(3), 276; https://doi.org/10.3390/aerospace13030276 - 15 Mar 2026
Viewed by 282
Abstract
The parafoil is highly susceptible to deviations from its reference trajectory under wind disturbances. Given its constrained longitudinal control authority, it has limited capability to correct these deviations and regain the intended glide path. To overcome this limitation, we propose a dynamic planning [...] Read more.
The parafoil is highly susceptible to deviations from its reference trajectory under wind disturbances. Given its constrained longitudinal control authority, it has limited capability to correct these deviations and regain the intended glide path. To overcome this limitation, we propose a dynamic planning framework based on a layered homing strategy. The airdrop mission trajectory is initially designed as a traditional multi-segment path. To approximate non-uniform glide characteristics under wind disturbances, this planning problem incorporates a predicted wind model as an external input. Node parameters of the segmented trajectory are then solved using an improved grey wolf optimizer (IGWO). By tracking this reference trajectory, the parafoil is guided into the proximity of the target. To ensure landing precision, the terminal phase is formulated and discretized using an adaptive pseudo-spectral method (APSM). The online planner computes a real-time trajectory to account for actual motion characteristics. This dynamic replanning (DRP) compensates for deviations caused by model mismatches and external disturbances. The proposed homing method is statistically verified via extensive Monte Carlo simulations under different wind conditions. Finally, the airdrop experiment is conducted to validate the DRP method. Full article
(This article belongs to the Section Aeronautics)
►▼ Show Figures

Figure 1

27 pages, 6061 KB  
Article
Servo-Elastic Control of a Flexible Airship with Multiple Vectored Propellers
by Li Chen, Lewei Huang and Jie Lin
Aerospace 2026, 13(3), 275; https://doi.org/10.3390/aerospace13030275 - 15 Mar 2026
Viewed by 238
Abstract
Owing to its large flexible envelope, an airship is highly sensitive to environmental disturbances, such as wind gusts. Fluid–structure interaction induces structural deformation, which modifies the aerodynamic force distribution and introduces additional coupling effects. Furthermore, servo-elastic deformation alters the position and orientation of [...] Read more.
Owing to its large flexible envelope, an airship is highly sensitive to environmental disturbances, such as wind gusts. Fluid–structure interaction induces structural deformation, which modifies the aerodynamic force distribution and introduces additional coupling effects. Furthermore, servo-elastic deformation alters the position and orientation of actuators mounted on the envelope, resulting in deviations between commanded and actual control forces. To address these issues, a composite control strategy integrating trajectory tracking and active elastic deformation suppression is proposed for a flexible airship equipped with multiple vectored propellers. Structural flexibility is explicitly incorporated into the dynamic model through modal decomposition, where the generalized coordinates and their time derivatives associated with deformation modes are included in the system state vector. A disturbance observer is developed to estimate actuator-level force deviations induced by elastic deformation, and the estimated disturbances are compensated in real time. Based on this formulation, a composite control framework, referred to as servo-elastic control, is established. The framework consists of a trajectory tracking controller and a displacement compensation module to achieve simultaneous motion regulation and structural deflection suppression. Numerical results demonstrate that the displacement at vectored thrust actuator attachment points is reduced to approximately 10% of that obtained using a trajectory tracking controller alone. The proposed method achieves significant deformation suppression without degrading position tracking performance, thereby enhancing control effectiveness and system stability of flexible airships. Full article
(This article belongs to the Special Issue Design, Characterization and Operations of Lighter-than-Air Flying Vehicles)
►▼ Show Figures

Figure 1

19 pages, 20315 KB  
Article
Experimental Quantization of Droplet Spatial Distribution in Icing Wind Tunnel with HACPI
by Letian Zhang, Boyi Wang, Yingchun Wu, Si Li, Zhiqiang Zhang, Xiangdong Guo, Xuecheng Wu, Quanzhong Xia and Zhen Liu
Aerospace 2026, 13(3), 274; https://doi.org/10.3390/aerospace13030274 - 15 Mar 2026
Viewed by 288
Abstract
The cloud spatial uniformity in the test section is crucial for icing wind tunnels in aircraft icing research and airworthiness certification. To achieve uniform supercooled large droplet (SLD) icing conditions, both the spatial variation in droplet size distribution and the concentration should be [...] Read more.
The cloud spatial uniformity in the test section is crucial for icing wind tunnels in aircraft icing research and airworthiness certification. To achieve uniform supercooled large droplet (SLD) icing conditions, both the spatial variation in droplet size distribution and the concentration should be considered. In this study, the spatial distribution of droplets under three SLD conditions is explored in the Aviation Industry Corporation of China Aerodynamics Research Institute (AVICARI)’s FL-61 icing wind tunnel. Measurements are conducted at 12 test points in vertical and horizontal directions using the holographic airborne cloud particle imager (HACPI) in conjunction with a two-axis traversing system. The droplet images obtained at specific test points below the test section centerline show deformation phenomena for droplets larger than 400 μm. Additionally, the aspect ratio of deformed droplets increases with droplet size. The spatial evolution of the median volume diameter (MVD) and liquid water content (LWC) is examined. For two spray arrangements where the activated nozzles are positioned close, the test point where the LWC peak in the vertical direction occurs is higher than that of the MVD peak. Further analysis focuses on the size distribution of droplets in the vertical direction. The results show that the settling effect of the droplets larger than 50 μm is evident under a flow velocity of 78 m/s. Meanwhile, the position where large droplets tend to appear lowers as the droplet size increases. Finally, the spatial uniformity of droplet size distributions at the same radial distance is discussed. Full article
(This article belongs to the Special Issue Deicing and Anti-Icing of Aircraft (Volume IV))
►▼ Show Figures

Figure 1

19 pages, 2147 KB  
Article
Dual-Mamba-ResNet: A Novel Vision State Space Network for Aero-Engine Ablation Detection
by Xin Wang, Hai Shu, Yaxi Xu, Qiang Fu and Jide Qian
Aerospace 2026, 13(3), 273; https://doi.org/10.3390/aerospace13030273 - 15 Mar 2026
Viewed by 266
Abstract
With the rapid development of the aviation industry, engines operate under extreme conditions of high temperature, high pressure, and high vibration, making them prone to surface damage such as ablation. Ablation not only affects the structural integrity of engine components but also threatens [...] Read more.
With the rapid development of the aviation industry, engines operate under extreme conditions of high temperature, high pressure, and high vibration, making them prone to surface damage such as ablation. Ablation not only affects the structural integrity of engine components but also threatens flight safety, making efficient and accurate detection of paramount importance. Traditional detection methods rely on manual visual inspection and non-destructive testing, which suffer from high subjectivity and low efficiency. In recent years, deep learning has achieved significant progress in industrial defect detection. However, conventional CNN-and Transformer-based architectures still suffer from substantial computational overhead and inadequate boundary segmentation accuracy in aero-engine ablation detection. This paper proposes a novel dual-pathway network Visual State-Space Residual Neural Network (VSS-ResNet) based on Mamba that combines Visual State Space (VSS) modules with ResNet50. This architecture leverages the global modeling capability of VSS modules and the local feature extraction capability of CNNs, effectively enhancing the accuracy and robustness of ablation boundary detection with the support of multi-scale feature fusion modules. Experimental results demonstrate that the proposed method achieves superior performance in mIoU, mPA, and Acc compared to mainstream segmentation models such as U-Net, Pyramid Scene Parsing Network (PSPNet), and DeepLab V3+ on a self-constructed engine endoscopic ablation dataset, validating its potential in intelligent aero-engine inspection. Full article
(This article belongs to the Section Aeronautics)
►▼ Show Figures

Figure 1

21 pages, 1796 KB  
Article
Research on Time Constraint Strategy of Flight Ground Support Operations Based on Causal Inference
by Xiaoqing Xing, Wenjing Wang, Hongyun Fan, Lei Xu and Mian Zhong
Aerospace 2026, 13(3), 272; https://doi.org/10.3390/aerospace13030272 - 13 Mar 2026
Viewed by 251
Abstract
To improve the punctuality of flight schedules, causal inference methods are introduced to model the potential causal structure and intervention effects among ground support operations of flights. The effectiveness of these methods in improving flight punctuality is verified under experimental conditions. When the [...] Read more.
To improve the punctuality of flight schedules, causal inference methods are introduced to model the potential causal structure and intervention effects among ground support operations of flights. The effectiveness of these methods in improving flight punctuality is verified under experimental conditions. When the causal relationship of Flight Ground Support (FGS) is determined, the research initiates from the perspective of FGS. A time-constrained strategy based on the Q-learning causal optimal strategy algorithm is proposed to transform causal effects into causal strategies. Initially, the influencing factors of FGS operations are classified into intervention groups. The causal effects of these influencing factors on their target support operations are calculated, and the influence degrees of the causes on the results within the causal relationship are investigated. Subsequently, the time constraint of the FGS process is characterized as a Markov decision process. The experimental results indicate that, compared with the traditional probability strategy, the causal strategy that considers the causal relationship enables over 51% of the flight plans to depart on time, with an average increase of 2.79%. The proposed method is not restricted to a specific airport or a single ground handling process configuration. Under the condition that ground handling operations are observable and sufficient historical operational data are available, it provides an interpretable optimization framework for time-constraint decision-making in flight ground handling operations across airports of different scales. Full article
(This article belongs to the Special Issue Emerging Trends in Air Traffic Flow and Airport Operations Control)
►▼ Show Figures

Figure 1

23 pages, 12572 KB  
Article
A Dynamics-Informed Non-Causal Deep Learning Framework for High-Precision SOP Positioning Using Low-Quality Data
by Zhisen Wang, Hu Lu and Zhiang Bian
Aerospace 2026, 13(3), 271; https://doi.org/10.3390/aerospace13030271 - 13 Mar 2026
Viewed by 304
Abstract
Low Earth Orbit (LEO) satellite signals of opportunity (SOP) provide a viable positioning alternative in GNSS (Global Navigation Satellite System)-denied environments, yet their accuracy is fundamentally constrained by the low-quality orbital data typically available, such as SGP4 (Simplified General Perturbations model 4) predictions [...] Read more.
Low Earth Orbit (LEO) satellite signals of opportunity (SOP) provide a viable positioning alternative in GNSS (Global Navigation Satellite System)-denied environments, yet their accuracy is fundamentally constrained by the low-quality orbital data typically available, such as SGP4 (Simplified General Perturbations model 4) predictions derived from Two-Line Elements (TLEs). To address this limitation, this paper proposes a dynamics-informed non-causal deep learning framework that enhances low-quality orbital data into high-fidelity trajectories for accurate SOP positioning. The proposed Non-Causal Dynamics-Informed Representation Temporal Convolutional Network (Non-Causal DIR-TCN) integrates phase space reconstruction and a Temporal Convolutional Network to explicitly model the chaotic dynamics inherent in LEO orbits, while relaxing the causality constraints of standard temporal convolutions to utilize both past and future context from the available SGP4 stream. Experimental results demonstrate that the framework significantly reduces orbit estimation errors and accelerates model convergence. When applied to LEO-SOP positioning, it achieves approximately 20% improvement in 2D positioning accuracy compared to conventional SGP4-based methods. This work effectively bridges the gap between accessible low-precision orbital data and high-accuracy state estimation, advancing the practical deployment of opportunistic signals for resilient positioning in challenging environments. Full article
(This article belongs to the Section Astronautics & Space Science)
►▼ Show Figures

Figure 1

31 pages, 15712 KB  
Article
Real-Time Anomaly Detection for Civil Aviation VHF Communications Using Learnable Kernels and Conditional GANs
by Junyi Zhai, Gang Sun, Zhengqiang Li, Quanxin Cao and Yufeng Huang
Aerospace 2026, 13(3), 270; https://doi.org/10.3390/aerospace13030270 - 13 Mar 2026
Viewed by 321
Abstract
Civil aviation VHF communication is safety-critical, yet operational links are routinely disturbed by atmospheric effects, aging hardware, and electromagnetic interference. The resulting anomalies are typically weak, intermittent, and extremely rare, which makes real-time detection difficult under strong temporal dependence and severe class imbalance. [...] Read more.
Civil aviation VHF communication is safety-critical, yet operational links are routinely disturbed by atmospheric effects, aging hardware, and electromagnetic interference. The resulting anomalies are typically weak, intermittent, and extremely rare, which makes real-time detection difficult under strong temporal dependence and severe class imbalance. We propose an end-to-end framework that couples (i) a learnable kernel projection for adaptive nonlinear feature extraction, (ii) a differentiable relevance–redundancy objective for feature refinement, and (iii) conditional temporal generation to augment minority anomaly patterns. A lightweight CNN–LSTM head is used for streaming inference. Training uses a mixture of operational anomalies and simulated degradation scenarios, while evaluation is conducted using operational data only. Experiments on 1.2 million VHF frames collected from real flight operations and ground station monitoring achieve an F1-score of 0.947, ROC-AUC of 0.972, and PR-AUC of 0.968, with an average inference latency of 34.7 ms. Full article
(This article belongs to the Section Air Traffic and Transportation)
►▼ Show Figures

Figure 1

26 pages, 18979 KB  
Article
Hierarchical Coupling/Disturbance-Utilization Control for Tiltable Quadrotors
by Tiancai Wu, Jie Bai and Min Xiong
Aerospace 2026, 13(3), 269; https://doi.org/10.3390/aerospace13030269 - 12 Mar 2026
Viewed by 262
Abstract
Tiltable quadrotors have the ability of independent control of position and attitude, which can be more flexible in complex task scenarios. However, the inherent unmodeled dynamics, model uncertainties, and external disturbances pose significant challenges to the control system design. Aiming at the the [...] Read more.
Tiltable quadrotors have the ability of independent control of position and attitude, which can be more flexible in complex task scenarios. However, the inherent unmodeled dynamics, model uncertainties, and external disturbances pose significant challenges to the control system design. Aiming at the the control problem of tiltable quadrotors, this paper proposes a hierarchical adaptive coupling/disturbance utilization control strategy. First, an error-dynamics model is developed, explicitly incorporating coupling effects and lumped disturbances. Then, hierarchical adaptive coupling/disturbance utilization mechanisms are designed to adaptively exploit coupling and disturbances to improve system performance. Subsequently, super-twisting higher-order sliding-mode observers and robust tracking control laws are synthesized to estimate lumped disturbances and guarantee system robustness. Finally, through theoretical analysis, the stability of the closed-loop system and the role of hierarchical adaptive coupling/disturbance utilization mechanisms are elucidated. The effectiveness of the proposed control strategy is validated through simulations and flight experiments. Full article
(This article belongs to the Section Aeronautics)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-92
Previous Issue
Next Issue
Back to TopTop