With the increasing complexity of aviation equipment and the transformation of maintenance modes， structural digital twin technology has become a key enabler for structural health management and predictive maintenance. Addressing common challenges in digital twin modeling-such as modeling assumption deviations， input uncertainty， and model response mismatch-this study proposes a residual-driven model optimization mechanism based on multi-parameter flight measurements. A dynamic closed-loop framework of “measurement–calibration–residual feedback–model correction” is established， with a rigorous theoretical proof of the residual feedback mechanism’s convergence and a quantitative analysis of error upper bounds. Furthermore， a multi-dimensional， quantifiable evaluation index system for model self-evolution is developed. Engineering verification， using the tail of a certain aircraft as an example， demonstrates that the proposed method effectively reduces model prediction errors under complex operating conditions and improves the accuracy and robustness of fatigue life prediction. The research outcomes provide theoretical support and methodological foundations for the engineering application and intelligent development of structural health management in aircraft.

The future battlefield is confronted with the problems such as high complexity of the environment， strong antagonism of the game， high real-time response， information incompleteness， and boundary uncertainty. To win the future aerospace battlefield， the manned/unmanned aerial vehicle cooperative combat system can become the core key due to its advantages of dual effectiveness， complementarities of combat weaknesses， and high efficiency of action coordination. This paper focuses on the research status of Manned/Unmanned Aerial Vehicle （MAV/UAV） cooperative combat， which is a new direction of high difficulty， rapid development， broad prospects in applications and multidisciplinary combat. The research status of manned/unmanned cooperative combat is summarized from three aspects： system concepts， key technologies and challenges. The definitions of system combat， winning mechanism and application process and the key technologies such as detection and situational awareness， mission planning， command and decision making， formation control， and effectiveness evaluation are expounded. Finally， the challenges of MAV/UAV cooperative combat in the future battlefield are prospected， and new ideas for the development of intelligent combat technology in the future are provided.

As an important part of aero engine， blade damage and maintenance have an important impact on aircraft operation safety and operating cost. To improve the maintenance quality and efficiency， scholars at home and abroad have carried out considerable theoretical and technological research on blade maintenance. To further analyze the maintenance process of damaged blades， firstly， the damage types and causes of fan blades， compressor blades， turbine blades and integral disk blades were summarized， and the maintenance technical routes under different damage conditions were analyzed in detail. The research field of in situ maintenance is weak. Therefore， the related technology and equipment of in situ maintenance are explained in detail， as well as the related optimization method and the application of new technology. Finally， the research and development direction of aero engine blade maintenance are prospected， which can provide reference for future researchers in this field.

Small object detection in UAV aerial images based on deep learning has a wide range of applications in military intelligence reconnaissance， battlefield surveillance and assessment， military object capture and verification， intelligent traffic management， infrastructure inspection and maintenance， disaster prevention and control， search and rescue， crop management and analysis， ecological protection and monitoring and other fields， and has become a current research hotspot in recent years. This review article gives a comprehensive and in-depth investigation on small object detection in UAV aerial images based on deep learning in the past five years. First of all， the definition and challenges of small object detection in UAV aerial images are introduced. Secondly， small object detection methods in drone aerial images are summarized in terms of discriminative feature learning， super-resolution technology， real-time lightweight detection， and other improvement ideas. Then， small object detection datasets of UAV aerial images are systematically summarized， and the performances of different algorithms are analyzed based on the VisDrone Challenge. Finally， the specific applications of small object detection in UAV aerial images in the military and civilian fields are comprehensively presented， and the potential future development directions of small object detection in UAV aerial images and some concerns about UAV aerial photography are also discussed. It is expected that this review would inspire relevant researchers to further promote the development of small object detection in UAV aerial images based on deep learning.

Multisource information fusion has undergone decades of development， expanding from classic signal processing issues to a multidisciplinary frontier field and covering a wide range of applications such as aerospace， intelligent transportation， industrial engineering， and security. This paper starts from the definition and principles of multisource information fusion， reviews the main development stages of information fusion technology， and summarizes the research progress of four basic scientific issues： fusion detection， fusion recognition， fusion estimation， and fusion association. The technology of multisource image fusion and machine learning methods oriented towards information fusion are also outlined. Based on this， the typical applications of information fusion in several fields are introduced. Finally， the development direction of information fusion technology and its applications are discussed.

With the rapid development of intelligent UAV technology， UAVs have the vast prospects in many fields， such as smart agriculture， post-disaster rescue， and battlefield reconnaissance. However， the limited perceptual and computing capabilities of an individual UAV make it difficult to meet the complex environment and task requirements in practice. Therefore， the efficient collaborative perception and computation of UAV swarms have become the main development direction in the future UAV field. In this paper， we first present the basic concepts of collaborative perception and collaborative computation. For the collaborative perception， we review the latest progress in swarm perceptual data collection and collaborative perception strategy. For the collaborative computation， the optimal schemes of computation task scheduling， resource allocation and data catching are summarized and compared. In addition， we discuss the urgent problems of collaborative perception and computation from the perspective of UAVs. Some potential research directions are presented， providing a reference for the follow-up researchers.

The concepts of collaborative combat Unmanned Aerial Vehicles （UAVs） have been widely discussed in recent years. Entities such as the United States， Russia， and Europe are competing in the development of UAVs featured by enhanced collaboration and high performance. A cutting edge hotspot for investigation on the corresponding key technologies is forming in the region of aviation equipment. The differences in usages， mission capabilities， and technological features of collaborative combat UAVs compared to traditional UAVs have sparked new discussions and reconsiderations. This paper traces the evolution history of military UAVs by focusing on the transformation of human-machine relationships and the expansion of UAVs’ capabilities. The development requirements emerged in the context of great power competition for future UAVs， as well as the capability demands and key technologies which give definitions on high-performance collaborative combat UAVs， are analyzed. Moreover， the design orientations that worth attention， such as autonomy/collaboration， decentralization/centralization and high performance/low cost， are discussed. Recommendations for future development of high-performance collaborative combat UAVs are also proposed.

In strong adversarial scenarios， Unmanned Aerial Vehicles （UAVs） often experience GPS malfunction due to interference， making it difficult to obtain their accurate position. Since UAVs often operate in formations or clusters， this paper proposes a strategy that relies on UAVs within the formation to measure relative spatial positions and locate each other， allowing UAVs to update their position information in real time even after GPS signal loss. Firstly， in response to the GPS-denied environment， the theory of the Partially Observable Markov Decision Process （POMDP） is introduced and the elements of POMDP are analyzed to establish a POMDP decision model based on collaborative positioning and scheduling is established. A belief state update method based on the Extended Kalman Filter （EKF）， as well as a Q-value estimation method based on Deep Q-Network （DQN） in deep reinforcement learning， is proposed to achieve accurate collaborative real-time positioning. Application tests in different scenarios show that the proposed model can achieve efficient management and scheduling of UAVs in formation， and can control GPS normal UAVs to effectively coordinate and locate GPS failed UAVs， which verifies the effectiveness of the model.

As the strategic equipment for a powerful country， aero-engines are considered as the integrations of precision processing and cutting-edge technologies. The development of aero-engine relies on the close cooperation of full lifecycles （i.e.， de-sign， manufacturing， testing， maintenance）， to meet the strict requirements like high-performance， high-reliability， and long service life， etc. Based on multi-source virtual assets （i.e.， data， models， and services） and multi-type digital technologies （i.e.， simulation， prediction， and optimization）， aero-engine digital twin engineering promises to explore the full lifecycle-based innovative modes and interdisciplinary collaboration-based efficient platforms. In this case， the capacities of aero-engines throughout their entire lifecycles can be greatly improved， giving new impetus for the accelerated development of entire chain in aero-engine industry. In this study， 18 challenges of aero-engine digital twin engineering are presented firstly； in addition， by reviewing the digital twin researches in aero-engine full lifecycles， the shortcomings on theories， software， and standards are revealed； thirdly， based on the 5D model of digital twin， ‘eye model’ architecture of digital engineering and architecture of digital experiment， testing and validation proposed by the authors’ team， the connotation， systematic framework and key technologies of aero-engine digital twin engineering are proposed； finally， several suggestions are provided to advance aero-engine digital twin engineering. The current efforts aim to illuminate pathways for enhancing the support capabilities in full lifecycles， and enabling a leap in digital/intelligent development for aero-engines.

Bird Inspired Flapping-wing Micro Aerial Vehicles （BIFMAVs） have great development potential in terms of flight efficiency， stealth， and maneuverability， exhibiting high research value and application prospects. This article mainly reviews the research and development progress of BIFMAVs over the past 20 years， summarizing and analyzing the current state of research on their overall design methods， aerodynamic analysis methods， and key technologies of the driven system and the flight dynamics and control. The characteristics and developmental trends of， and the challenges faced by each technology are presented， and the prospects for the future development direction of BIFMAVs are ultimately proposed. By providing a comprehensive review of the current state of research and development direction of key technologies for BIFMAVs， it can serve as a reference for subsequent researchers working in this field.

With the rapid development of China’s low-altitude economy and the planning requirements outlined in the “14th Five-Year Plan”， low-altitude transportation is expected to become a significant mode of transport. However， the current low-altitude airspace remains largely undeveloped and not fully open in China. As a result， related studies on airspace and trajectory planning are still in their early stages， and are difficult to meet the surging demand for low-altitude operations. Therefore， it is essential to establish a robust and comprehensive theoretical framework for airspace and trajectory planning according to the unique characteristics of low-altitude environments. This paper firstly examines the fundamental characteristics of low-altitude airspace and systematically reviews the research on the limiting factors of low-altitude airspace planning， airspace designation， and trajectory planning both domestically and internationally. Existing findings and gaps in current research are discussed， and common challenges in the field are also highlighted. Next， the feasibility of employing block or tube airspace designation methods is assessed in the context of China’s current low-altitude development. A developmental trajectory that evolves from individual trajectories to trajectory clusters and ultimately to trajectory networks is proposed， emphasizing the need for accelerated technological integration to innovate airspace infrastructure. Finally， this paper outlines three key elements that should be prioritized for future low-altitude airspace and trajectory planning： first， incorporating environmental and social factors as central elements in airspace planning； second， exploring phased airspace designation， composite designation strategies， and specialized planning methods； third， designing generalized fast algorithms for trajectory planning to accommodate diverse operational scenarios.

The assessment of hypersonic flight technology at home and abroad always relies on flight tests， which are time-consuming and expensive， and have posterior risks. The development of advanced hypersonic ground test facilities has been a fundamental research topic in aerodynamics frontier for decades； however， the existing test facilities are still inadequate for the required technology development of air-breathing hypersonic engines at high Mach numbers. The successful development of the JF-22 hypervelocity wind tunnel under the National Major Scientific Research Instrument Project supported by the National Natural Science Foundation of China is a major breakthrough in this area. This paper first reviews the research background of the hypersonic wind tunnel and introduces the four basic requirements of the wind tunnel based on engineering practice. Considering thermo-chemically reacting gas flows， the necessity of revolutionary change of the wind tunnel test simulation criteria of experimental aerodynamics from “flow similarity simulation” to “flight condition reproduction” is discussed. Then， the theories and technologies for detonation-driven hypervelocity shock tunnels are systematically expounded， and the engineering problems solved with the theories and technologies are also discussed. Finally， the technology system of the JF-22 hypervelocity wind tunnel， developed on the basis of these theories is summarized and evaluated with the JF-22 calibration results. These results not only verify the theories of detonation-driven hypervelocity shock tunnel， but also show a comprehensive assessment of the JF-22’s technology system. The success of the JF-22 hypervelocity wind tunnel is a new milestone in developing advanced hypersonic test facilities. The JF-22 remarkable performances， such as high flow velocity， high total temperature and high stagnation pressure， and wide speed range and altitude are of significance for supporting the research on air-breathing hypersonic engines， aerospace aircrafts， and the frontier of high-temperature gas dynamics.

The rapid development of Unmanned Aerial Vehicle （UAV） technology has led to its continuous expansion in military and civilian fields， gradually becoming a powerful engine driving the development of low-altitude economy. Among the core components of UAVs， the satellite navigation system provides precise positioning and navigation information. However， due to the vulnerability of the satellite navigation system， satellite navigation often faces severe challenges brought by complex electromagnetic environments， causing UAVs to lose their positioning ability or deviate from the planned route， thereby seriously threatening flight safety and mission success rate. This paper systematically reviews the research status of anti-jamming technology for UAV satellite navigation systems. Firstly， starting from the main navigation interferences faced by UAVs， it analyzes the impact of oppressive interference and deception interference on UAV navigation systems. Secondly， it comprehensively summarizes the anti-jamming methods of UAV satellite navigation terminals. Regarding anti-oppressive interference， this paper focuses on discussing the technological progress at the receiving antenna end， radio frequency front end， and signal processing end. In terms of anti-deception interference， the methods of enhancing receiving processing capabilities and using advanced algorithms to detect and suppress deception interference are analyzed. In addition， the study studies the anti-jamming methods for UAV navigation in denied environments， including inertial navigation， visual navigation， celestial navigation， ultra-wideband， magnetic field navigation， radar navigation， and multi-information fusion navigation technologies. Moreover， for the formation navigation of multi-UAV clusters， the methods of inter-UAV cooperative and system improvement were explored to enhance the anti-interference capability of the entire UAV group. Finally， this paper identifies the current problems， outlines future research directions， and discusses potential technological advances. The research results of this paper not only provide a reference for the continuous progress of UAV navigation anti-jamming technology， but also offer theoretical and practical guidance for academic exploration and engineering application in related fields.

As one of the most promising types of Unmanned Aerial Vehicles （UAVs） powered by new energy sources， hydrogen-powered UAVs are closely linked to the concept of green aviation and low-altitude economic scenarios. To provide a reference for the design of hydrogen powered UAVs， this paper summarizes the key areas and technical issues involved in the development of hydrogen powered UAVs， and reviews relevant research. The review first outlines the development history， technical advantages， application scenarios， and common examples of hydrogen powered UAVs. Subsequently， it categorizes and discusses the key issues related to hydrogen powered UAVs in four major technical areas： overall design technology， structural design technology， power system design technology， and flight control technology. Moreover， the technical frontiers faced in each area and the current research conducted by researchers both domestically and internationally are analyzed. Finally， combining the relevant technological advancements， the paper proposes suggestions and outlooks for the development of hydrogen powered UAVs. The research indicates that the development potential of hydrogen powered UAVs has not been fully explored， and joint efforts across multiple disciplines and fields to leverage hydrogen’s crucial role in extending UAV endurance are required so as to reduce onboard weight， and promote green aviation development.

As a strategic emerging industry， low-altitude economy is a new track for industrial development and a new engine for economic growth. Urban Air Mobility （UAM） is an important part of low-altitude economy. To gain insights into the key technological research trends and development dynamics within the UAM sector， identify hot topics of research， and unveil the knowledge structure and research scope in Urban Air Mobility. This includes exploring the technological evolution pathways and future application prospects to acquire a profound understanding of the current state of Urban Air Mobility research. A bibliometric analysis was conducted on data retrieved and extracted from the Web of Science Core Collection （WoSCC） database. From the result， UAM research forms a comprehensive framework from technology （e.g.， collision avoidance， high-precision positioning， plus-cruise vertical take-off， dynamic airspace sectorization， etc.） to operations （e.g.， urban air mobility operations， unmanned aerial vehicle logistics route network， hyper-local weather prediction） low-noise landing conditions and consumer intention. The aim is to achieve a safe， efficient， and environmentally friendly urban air traffic system， key technologies that face the unique challenge of addressing the complexity of low altitudes in cities， and the importance of air traffic management and environmental impact should be strengthened during the development of the urban air mobility.

Cooperative technology is the effective guarantee and approach for swarm systems to execute tasks and generate intelligence. The core of intelligent cooperation of swarm systems lies in the information exchange between individuals to complete complex cooperative behaviors， thereby achieving a significant improvement in overall task efficiency. By sorting out the functions and supporting relationships required for cooperative task execution in swarm systems， five key technologies required for swarm systems to complete tasks cooperatively are summarized. They are self-organizing interaction technology， cooperative perception technology， cooperative cognitive technology， cooperative decision-making technology， and cooperative guidance and control technology. An Interaction-Observation-Orientation-Decision-Action （IOODA） technology architecture for intelligent cooperation in swarm systems is proposed. The concept and connotation of the intelligent cooperative IOODA technology architecture for swarm systems are presented. The key technologies involved in the IOODA technology architecture and the existing progress are reviewed. The challenges faced by the IOODA technology system are analyzed， and prospects for future development of various key technologies are also discussed.

In the future， urban low altitude may face a large number of demands for operation of electric Vertical Take-Off and Landing （eVTOL）， which will result in potential problems of low airspace utilization， high collision risk， etc. To ensure the safety and efficiency of aircraft operation， it is necessary to establish appropriate safety interval standards. To study the safety interval of multi-model eVTOL in urban low altitude， a classical Event longitudinal， lateral and vertical collision model is established for composite-wing eVTOL， and an improved Event model based on the frustum of the cone collision box is established for multi-rotor eVTOL. The eVTOLs are classified into three categories of light， medium and heavy types according to their payload and number of passengers. The mainstream models are selected for statistical analysis， and the collision box sizes of the models are calculated. Considering the positioning error， the longitudinal， lateral and vertical overlap probability of the aforementioned parameters is calculated using the concept of Required Navigation Performance （RNP）. A simulation environment is established to calculate the parameter of relative velocity， taking into account the distribution of heading angle， pitch angle limitation， and velocity error distribution. Finally， the lateral， longitudinal and vertical safety intervals of different types of eVTOLs are calculated according to the established collision model. The target level of safety of light， medium and heavy eVTOL are set to 10^-7， 10^-8 and 10^-9 times/flight hour， respectively. The minimum intervals between different types of eVTOL are finally derived. These intervals are determined to be 82， 83， 93， 102 m， respectively， for light multi-rotor， light composite wings， medium composite wings， and heavy composite wings. The results of the study can provide a reference for the development of eVTOL interval standards.

Flying wing configuration aircraft pursues excellent aerodynamic and stealth performance. However， traditional mechanical control surfaces can compromise its stealth profile and may lead to a decrease in control effectiveness at moderate angles of attack， potentially causing aircraft instability and loss of control. Active Flow Control （AFC） techniques effectively address the aforementioned drawbacks. In this study， a wind tunnel virtual flight test system， integrated with closed-loop active flow control， is constructed. The system is capable of simulating active flight attitude control of controlled model under both steady and unsteady incoming flow conditions. Utilizing this system， wind tunnel virtual flight tests of the flying wing configuration model with AFC are conducted， obtaining its three-axis attitude control characteristics under steady flow conditions. Results demonstrate that consistent and controlled pitch and roll moments can be generated through trailing edge circulation control， while required yaw moment can be generated through wingtip reverse jets， achieving stable three-axis attitude control of the flying wing aircraft. Particularly， when controlling longitudinal attitude of the model with pitch circulation control， the generated pitch moment is linearly correlated with jet momentum coefficient. Furthermore， a closed-loop control strategy for gust load alleviation based on model longitudinal attitude feedback is proposed. The stability enhancement ability of AFC for flying wing configuration model under gust disturbance is validated. Additionally， it is further discovered that the effectiveness of the stability enhancement control is jointly determined by the intensity of the jet applied for control and the phase relationship between the control signal and the gust disturbance.

Thrust vectoring technology is a key technology for future aircraft， especially high-maneuverability aircraft. The core component of the technology is the thrust vectoring nozzle. The fluidic thrust vectoring nozzle achieves airflow deflection at the nozzle outlet， and has many revolutionary advantages. It can further derive various functions such as short distance/vertical takeoff and landing and reversing thrust to adapt to more diverse application scenarios. Through decades of research， the fluidic thrust vectoring nozzle has gradually gone through stages such as conceptual conception， preliminary exploration， mechanism research， and engineering experiments， continuously improving its technological maturity and developing towards preliminary engineering applications. This paper focuses on introducing the research achievements of representative domestic and foreign researchers on various fluidic thrust vectoring nozzle in recent years. It explores the development trends and future research priorities of fluidic thrust vectoring nozzle， and points out that it is necessary to further strengthen the research on the mechanism of the internal flow field， overcome key technologies such as multi-objective and multi-disciplinary comprehensive optimization， and the overall matching of the aircraft， engine and fluidic thrust vectoring nozzle. By promoting engineering applications， it is expected to provide a reference for the application of fluidic thrust vectoring nozzle technology.

The distributed ducted fan power system is considered as one of the most potential power systems for the next generation civil aircraft design. The complex aerodynamic coupling between ducted fan group and wing/flap and the influence law of propulsion performance restricts the development of new concept distributed electric propulsion vehicle. Using CFD numerical simulation and ground test， this paper studies the aerodynamic configurations and parameter influence mechanism of distributed ducted fans， such as the single ducted fan， ducted fan group， ducted fan group with flap. The distance between non-fusing ducted fan groups， the shape of fusing ducted fan groups， the number of ducted fans， and the influence of the jet flow on the propulsion performance of the ducted fan groups are analyzed to explore the effects of different configurations of distributed culvert power system on propulsion efficiency， thrust distribution and blade load in hover and vertical take-off and landing states. The results show that the influence of the dynamic configuration of distributed ducted fan on the propulsion performance is about 3%–5%. The transverse compact distributed ducted fan can reduce the angle of attack of the incoming air flow between adjacent ductwork and reduce the propulsion efficiency， and the inner culvert is affected most obviously. The convergence of culvert fan group causes the distortion of air flow into the culvert and the flow separation at the expansion section of the culvert top， resulting in reduction of force effect. In the vertical take-off and landing stage， the near-surface jet increases the blade thrust and consumes power and decreases the ducted thrust， and the inner ducted is affected most obviously. With the increase of the distance from the ground， the effect of jet decreases gradually and the loss of force decreases.