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.

Lightweight is a substantial theme in the research and development of aerospace and aeronautical equipment due to its decisive impact on the comprehensive performance and operational efficiency of the equipment. Over the past decades， a handful of innovative optimization design approaches， emerging high-performance materials， and revolutionary manufacturing technologies have been uninterruptedly developed， and the level of lightweighting in aerospace and aeronautical equipment has been significantly advanced. However， the increasing demands for comprehensive performance and multifunctionality of the next generation of equipment present serious challenges to existing lightweight design and manufacturing technologies. Therefore， with a particular emphasis on the layout design， electromechanical system design， materials and structures， high-performance manufacturing and assembly， this paper analyzes the posed challenges and future perspectives.

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.

Morphing aircraft， capable of real-time shape deformation according to task requirements and flight conditions to achieve optimal flight performance， has emerged as a significant direction for the future development of aircraft. This paper reviews the research status of deformation modes and key technologies of aerodynamic layout design for morphing aircraft. Firstly， the development of morphing aircraft can be divided into two stages by the progression of time： the mechanical deformation stage and the flexible and muti-dimensional deformation stage. Then， this article summarizes morphing solutions for different parts of the aircraft， namely， the head deformation， wing deformation， power plant deformation， and combined deformation. It particularly explores the developmental history of various wing morphing schemes， discusses their applications in different aerodynamic configurations including variable sweep wing， variable forward sweep wing， folding wing， telescopic wing， oblique wing， continuous variable curvature wing， and analyzes their aerodynamic and stability characteristics， respectively. Next， the implementation objectives of morphing aircraft are summarized and divided into three types： single domain optimal variable configuration， multi-domain fusion variable configuration， and one vessel multi-energy variable configuration. Subsequently， compared with fixed shape aircraft， the key technical challenges in aerodynamic layout and overall coordination design， time-varying aerodynamic effect evaluation， aerodynamic layout scheme optimization， and multidisciplinary coupling design derived from the implementation of morphing aircraft are analyzed， with particular focus on the research progress and current status of dynamic aerodynamic calculation methods and aerodynamic optimization design technologies for morphing aircraft. Finally， the future research direction and development prospects of morphing technologies are envisioned. Targeting at the needs of wide velocity domain and large airspace flight， exploring new conceptual deformation methods that can improve the performance of multiple flight missions and establishing intelligent morphing design model and multidisciplinary strong coupling integrated design system will become important development trends.

The future operational environment imposes higher and more comprehensive requirements for the performance of fighters， calling for deeper integration between fighter airframe and engine and closer collaborative design during fighter research and development. Building on theories and practices for optimum airframe-engine integration in fighter design in the past decades， this paper proposes a collaborative airframe-engine design concept. Through an analysis of the combat requirements of Penetrating Counter Air （PCA） and other operational concepts， this paper then presents the essential capabilities of high performance fighters and looks into the requirements of future-oriented collaborative airframe-engine design. The key technologies concerning flight performance， stealth characteristics， flight control and aircraft energy are discussed， and the possible implementation approaches and suggestions for design and research are also provided.

Aeroengine amalgamates state-of-the-art technologies across diverse domains， serving as a comprehensive manifestation of a nation’s prowess in science and industry. Frequent malfunctions occur due to its complicated structure and harsh service environment. Therefore， it is essential to employ prognostic and health management technology to provide crucial support for aviation safety and reliable operations. As vibration faults constitute a primary failure mode in aeroengine， this paper， grounded in this premise， systematically reviews and analyzes existing vibration monitoring and fault diagnosis for aviation engines both domestically and internationally. The analysis is categorized into three dimensions， covering the application of overall vibration monitoring and diagnostic systems， typical fault characteristics and diagnostic methods， and the overall vibration fault diagnostic technology， including dynamic analysis， signal processing techniques， and relevant technologies such as deep learning. Then， the problems and challenges faced by the existing vibration fault diagnosis of aeroengine are identified. Furthermore， future development goals are provided.

The development of electric Vertical Take-off and Landing （eVTOL） aircraft is greatly promoted for the advances in battery and motor technologies and the application of distributed electric propulsion system. In this paper， the advantages and disadvantages of different eVTOL configurations and their application scenarios are summarized， and a comprehensive comparison between eVTOL and conventional fuel aircraft is made in terms of performance， noise and cost. The interaction noise by rotors and rotor-wing is more prominent for eVTOL， but the electric propulsion rotor system with low tip speed and large rotor solidity greatly reduces its noise level （about a reduction of 15 dB）. Lithium-ion batteries are the main energy source for current and future eVTOL. The advanced battery material system， integrated design of battery-structure and excellent battery management system are effective ways to improve the energy density and energy security of the whole aircraft in the future. The redundant manipulation of eVTOL increases the difficulty of flight control system design， but improves the safety of the whole aircraft at the same time. Fault reconstruction and collaborative control are new challenges faced by eVTOL. A wide variety of configurations and novel design features such as high voltage power， electric propulsion， flight-by-wire flight system and electric actuation are proposed for eVTOLs. In the absence of flight test data， the system-based method is the main method for safety design of eVTOL.

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.

Since the 1950s， scramjet has been regarded as a goal of the hypersonic propulsion system in the aerospace field， and extensive research work has been conducted in both theory and practical technology. At the beginning of the 21st century， the United States made a series of technological breakthroughs close to practical applications， pushing the research and application of the scramjet technology to a new stage. This paper briefly describes the working principle of the scramjet， discusses the difficulties and latest progress in key technologies such as dual-mode working process， hypersonic compression flow， supersonic combustion， ultra-high temperature structure and thermal protection， ground test and numerical simulation， and expounds the understanding and suggestions on the development direction of key technologies such as wide speed range， repeatability， and higher Mach number of scramjet.

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.

Low-Altitude Intelligent Network （LAIN）， as a new type of intelligent network， relies on space-air-ground-sea facilities to constitute a digital intelligent network system. It is a key component of the space-air-ground integrated network， and can support the seamless and ubiquitous connections of the sixth generation communication technology and promote the development of intelligent network service from ground to low-altitude space. However， LAIN is still in the developing stage and faces the following key challenges： intractability of aerial control， severe spectrum interference， and multi-dimensional resource limitation. This article focuses on the issues of LAIN architecture and safety control， including the current development status of low-altitude network and its significance for industrial technology transformation. Then， from the perspective of spectrum resources， network resources， and airspace resource management， the recent related works are analyzed. Furthermore， we analyze the key technologies such as low-altitude aircraft air-ground spectrum sharing， sensing， transmission， computing networking coverage， low-altitude airspace intelligent supervision， and point out future development directions. Finally， an application demonstration of LAIN is proposed， aiming to satisfy the significant requirements for efficient operation and safety in low-altitude airspace， and providing the theoretical basis as well as technology for the further development of the next generation space-air-ground integrated network.

Reusable launch vehicles are an important way for humans to enter and exit space on a large scale and at a low cost. Starting from the technical requirements of vertical takeoff and landing reusable launch vehicles， this paper summarizes the technical challenges faced by vertical takeoff and landing reusable launch vehicles， and analyzes the key technologies of vertical takeoff and landing reusable launch vehicles. The research progress and future development directions of key technologies for vertical takeoff and landing reusable launch vehicles are then discussed in terms of overall optimization design， power， structure and thermal protection， navigation， guidance and control， and health management， which can provide reference for the technical research of reusable launch vehicles.

Technological breakthroughs have once again spawned a lot of attention to the commercialization of Urban Air Mobility （UAM） in urban low-altitude airspace. The urban low-altitude airspace environment is complex， the density of urban air traffic flow in commercial scenarios is high， and the specifications of vehicles are not uniform. As a new infrastructure for UAM， low-altitude public routes are an important means for UAM to carry out refined management. However， the planning methods of low-altitude public routes， the required infrastructure， and the urban air traffic operation and control mode are still unclear. In response to the above issues， this article sorts out the basic concepts and development history of UAM and low-altitude public air routes， as well as UAM management based on low-altitude public air routes； In addition， an UAM operation management framework is proposed. Suggestions and countermeasures are provided on the possible responsibilities of relevant administrative departments in the development UAM； Finally， the construction method of low-altitude public routes network， the difficulties in the development process of UAM and implementation suggestions are summarized， in order to shed light on the healthy and orderly development of the UAM.

Fiber reinforced polymer composites are of great significance for improving the thrust-to-weight ratio， fuel economy and environmental protection of aeroengines. This paper introduces the applications of polymer composites in aero-engine. The key challenges and technologies of composites-based fan case and fan blades including the design technology of preforms with complex shapes， high-precision manufacture technology of special-shaped composite structures， multi-scale and high-fidelity modeling method of composites， and the containment design criteria for composites fan cases are summarized. Drawing on the recent research hotspots， new ideas and technologies for composite aero-engine structures are prospected.

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.

Unmanned Aerial Vehicle （UAV） swarm warfare is rapidly developing towards intelligence and practicality， which will pose a huge threat on the future battlefield. Therefore， research on detection and tracking of anti-UAV swarm is imperative. To solve the problems of reduced detection and tracking accuracy caused by mutual occlusion between UAV swarm and weak targets in complex scenes and long-distance detection conditions， this paper proposes a UAVS-Multiple Object Tracking （UAVS-MOT） multi-object continuous robust tracking algorithm. The UAVS-MOT model is based on the multi-branch anchor-free frame prediction structure of the FairMOT model. The coordinate attention module is combined with the DLA-34 network to construct a new backbone feature extraction network， so as to improve the expression ability of feature information. In addition， the new ArcFace Loss function is introduced for training to improve the convergence rate of the model， and the BYTE data association method is used to reduce the target miss rate and improve the track consistency. The experiment shows that the Multiple Object Tracking Accuracy （MOTA） and Identity F1 Score （IDF1） of the proposed algorithm on the UAVSwarm Dataset are 73.4% and 76.1%， respectively， which are 5.7% and 2.9% higher than those of the original FairMOT algorithm. The proposed method can solve the problems of missed and false detection of targets and low tracking accuracy， and has good robustness.

Unmanned Aerial Vehicles （UAV） have been widely used due to their advantages of small size， light weight， and simple operation. The combination of the deep learning method and UAV system can help to quickly and accurately detect the desired target on UAV aerial images with high definition and a wide field of view. Related topics have become one of the current research hotspots. This paper reviews the research progress of deep learning methods for object detection and semantic segmentation in UAV aerial images in the past ten years. First， the characteristics and wide range of application scenarios of UAVs and their aerial images are summarized， and the development process of target detection and semantic segmentation methods for UAV aerial images is briefly described. Then， the object detection and semantic segmentation methods of UAV aerial images based on deep learning are classified according to different network models， and their improvement strategies， application scenarios， contributions， and limitations are summarized. Subsequently， the data sets of aerial images taken by UAVs in recent years are collected and sorted out， and the evaluation indicators of commonly used convolutional neural network models are summarized. Finally， the existing problems in this field are pointed out， and prospects for future research trends are presented.

Tiltrotor aircraft is a significant trend in the development of the next generation of rotorcraft. It integrates the advantages of rotorcraft and fixed-wing aircraft， but also introduce more complex problems in terms of aerodynamics， structural dynamics， flight dynamics， and aeroelastic coupling. The wind tunnel experiment is an important technical method to understand and investigate the key aerodynamic， structural， and flight issues of tiltrotors. This paper give a comprehensive overview of a large number of wind tunnel tests in the development process of tiltrotor aircraft in China and other countries， and provides various types of test simulation criteria， equipment and facilities， typical results， and main conclusions of tests for tiltrotor aircraft rotors and corresponding airfoils， rotor/wing aerodynamic interference， rotor/wing aeroelastic stability， virtual flight， etc. Considering the research and development requirements， this paper also proposes suggestions for the development of wind tunnel testing technology for tiltrotor aircraft in China.

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.

The compound high-speed unmanned helicopter consists mainly of the aerodynamic components such as rotor， wing， propeller， fuselage， and horizontal & vertical tails. Aerodynamic interferences between components can be complex and vary rapidly with the forward flight speed. To achieve a high level of model confidence， it is necessary to correct the flight dynamics model parameters according to the forward flight speed. Besides， the flight control scheme must be adjusted accordingly to achieve stable and controllable flight throughout the entire speed envelope. A model for the flight dynamics of the compound high-speed unmanned helicopter is presented. The model is corrected based on wind tunnel trimming tests to enhance the confidence of the mathematical model. At the trimming point， the non-linear dynamics model is linearized to obtain the evolution of the open-loop dynamics with the forward flight speed. The effect of the control augmentation system on the closed-loop steering stability performance is also evaluated. Based on the classical control approach， a set of practical feed-forward compensation， loop weighting， and control allocation schemes are designed considering the lift， thrust， and yaw characteristics of the compound high-speed unmanned helicopter. Simulation and test flight verification are carried out to confirm the effectiveness of these schemes. The results show that the proposed nonlinear dynamic model has high confidence， and the consistency between the trim results of the mathematical model and wind tunnel tests is good. The distribution of eigenvalues of the high/low-order linear models is basically consistent and the maneuver response characteristics are in good agreement with the nonlinear dynamic model. The flight simulation preliminarily validates the effectiveness of the compound scheme for lift， thrust， and yaw. The successful flight test of the first 300 kg prototype in China validates the compound flight control scheme in hover and low-speed flight.