UCAV Research Articles

Flight dynamics modelling and simulation of a tailless UCAV lambda wing configuration

Purpose This research work aims to develop and validate a flight dynamics model for an unmanned combat aerial vehicle (UCAV) that has a tailless flying wing configuration with a lambda wing planform. This study includes the generation of complete aerodynamic data by both computational fluid dynamics (CFD) and US Air Force (USAF) DATCOM methods to facilitate six-degree-of-freedom (6-DOF) flight simulation, providing an understanding of the aircraft’s performance. Design/methodology/approach The UCAV model was developed using 3D CAD modelling in SolidWorks, referencing SACCON geometric properties. Stability, control and dynamics derivatives of the UCAV model are generated using CFD and DATCOM methods and then validated with wind tunnel experimental data. 6-DOF flight simulations are conducted using both DATCOM and integrated CFD-DATCOM approaches. Findings The analysis is presented at various angles of attack and sideslip angles. CFD analysis provided static stability derivatives, and USAF DATCOM methods computed static stability, control and dynamics derivatives. Flight simulation results are compared, and the integrated CFD-DATCOM approach demonstrated greater accuracy and reliability, particularly for steady-state pitch responses and dynamic stability. The pitch attitude controller enhanced system stability, reduced steady-state error and improved overall performance. Research limitations/implications This present research study should consider transonic and high-speed performance aspects and also implement an automatic robust controller for UCAV flight performance analysis. Practical implications This research work can be useful for developing a variety of control strategies for a tailless UCAV, including different combat missions in a flight simulation scenario. Originality/value UCAV flight dynamic data is limitedly available for flight simulations in the literature, particularly for tailless UCAV configurations. This study contributes by obtaining such data through integrated CFD-DATCOM methods. The 6-DOF flight simulation was set up in MATLAB Simulink using an indigenously developed UCAV flight dynamic model.

The Origin and Evolution of Military Drone (UAVs) Technology in Warfare Equipment in Africa

Abstract The development of unmanned aerial vehicles (UAVs) could potentially revolutionise how military force is used in the future. While early operational experiences with UAVs show that this operation is promising, its full range of capabilities is largely unknown. Over the years, the application of drones has shifted from traditional methods of application to a much more modern one. Despite this evolution, the process of normalising drones throughout Africa has received little scholarly attention. The purpose of this paper is to analyse the historical origin and the evolution of military drones in the theatre of conflicts in Africa. The results arrived at in this paper have been thanks to a consortium of multinational academic literature embodied with the historical methods of analyses. Besides the conceptual framework of the study, this paper examines the historical origin of military drones, their mapping and evolution in Africa, and their humanitarian impacts as well as their limitations. From our findings, state and non-state actors have been actively involved in the usage of modern military drones in Africa during armed conflicts for the last two decades, and this is in an attempt to have a complete mastery over the conflict map. Keywords: UAVs, military drones, Africa, armed conflict, security.

An interdisciplinary study of the effect of laser radiation on carbon fiber-reinforced polymer, in the context of counteracting unmanned aerial vehicles

This article presents an interdisciplinary study that combines historical analysis and experimental research to explore the vulnerability of military drones made from carbon fiber-reinforced polymer to destruction by laser radiation. The work is structured around two interconnected areas: the historical evolution of carbon fiber-reinforced polymer use in military drone construction and the parallel development of high-energy laser systems as precision countermeasures. The historical section traces the trajectory of carbon fiber composites from their initial applications in aerospace and defense industries during the late 20th century to their widespread adoption in military unmanned aerial vehicles, driven by the need for lightweight, durable, and radar-evading materials. Special attention is given to geopolitical, technological, and strategic factors that influenced the increasing reliance on carbon fiber-reinforced polymer for enhancing drone performance in terms of range, payload, and survivability. In parallel, the article examines the emergence of directed energy weapons, focusing on laser systems, as a response to the limitations of conventional kinetic countermeasures in neutralizing fast, small, and low-observable drones. The study outlines how the military’s growing concern with swarm attacks and stealth unmanned aerial vehicles has accelerated investments in laser-based air defense systems capable of engaging airborne targets with high accuracy and low operational cost. The experimental component investigates the mechanisms of laser-induced damage in carbon fiber-reinforced polymer materials through controlled laboratory tests, during which samples are exposed to varying intensities and durations of laser radiation. The results are analyzed to determine the energy thresholds and exposure conditions that lead to effective material destruction. By synthesizing historical and experimental data, the article provides a comprehensive understanding of how past material choices have shaped current vulnerabilities in drone technology and how modern laser systems are specifically adapted to exploit those weaknesses. This integrated approach not only bridges the gap between history and applied science but also contributes to the development of more effective and informed counter-drone strategies in contemporary and future military operations.

Low Cost Drones in Modern Warfare and Counter Drone Strategies: A Review

his review article discusses low-cost military drones, the components necessary to manufacture such a drone, its overall cost, and the threats posed by them against civilian and military targets. It considers available counter-drone technologies, examining their challenges and costs. While conventional air defense systems defend against single targets very well, defending against drone swarms will overwhelm any single missile defense solution. They are often stationary and fixed in place for easy targeting and destruction. Low-cost interceptor drones might be the answer to this dilemma. Kinetic-kill approaches seem to be the best solution, considering how inefficient jamming and cyber-attacks are and how ridiculously expensive interceptor missiles are. This paper discusses the components needed to develop interceptor drones, the deployment processes, and the strategic shift that must be made to embrace low-cost counter-drone technologies for the battlespaces of tomorrow.

Ethical and Security Risks of Autonomous AI Systems

As AI systems grow more independent, the challenges of keeping them both ethical and secure are only getting tougher. From self-driving cars and military drones to algorithms making real-world decisions, these technologies often operate with little—or no—human input. This paper takes a close look at the risks that come with that shift. On the ethical side, we’re talking about things like bias, unclear accountability, and the risk of sidelining human judgment. On the security front, there’s the threat of adversarial attacks, hacking, and deeper system flaws that could be exploited. By reviewing what’s already out there—research, case studies, real-world examples—we aim to unpack how these risks are currently being managed. More importantly, we offer ideas on how future systems can be built with stronger guardrails, both in terms of tech and governance.

Evaluation of unmanned combat aerial vehicles using q-rung orthopair fuzzy entropy based multi-attribute border approximation area comparison method

Unmanned combat aerial vehicles (UCAVs) have become an indispensable part of modern military operations. As they can be used for both defensive and offensive purposes, they play a crucial role in shaping military strategies and improving the operational capabilities of security forces. Many countries are investing in UCAV technology and placing these vehicles at the centre of their defence strategies. Choosing the right UCAV enables a country to strengthen its national security and its position in international relations by enhancing its defence capabilities. This study considers the evaluation of UCAVs as a multi-criteria decision making (MCDM) problem. In the study, the q-ROF (q-rung orthopair fuzzy) entropy-based MABAC (Multi-Attribute Border Approximation Area Comparison) method is proposed as a new integrated MCDM technique to solve the problem. The theoretical framework of the proposed method is explained in detail and applied to an UCAV selection problem. In practise, fourteen different UCAV alternatives were evaluated based on nine criteria (length, wingspan, height, empty weight, maximum takeoff weight, payload capacity, maximum cruising speed, maximum altitude, duration in the air). As a result of the application, the best-performing alternative was identified as UCAV-9 (A9). In addition, the results of the proposed method were compared with the results of the classical q-ROF MABAC, q-ROF MAIRCA (Multi Attributive Ideal-Real Comparative Analysis), q-ROF TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), q-ROF CRITIC-EDAS (Criteria Importance through Inter-criteria Correlation-Evaluation based on Distance from Average Solution), and q-ROF BWM-MARCOS (Best–Worst-Method-Measurement of Alternatives and Ranking according to COmpromise Solution) methods. UCAV-9 (A9) emerged as the strongest alternative based on the comparison analysis. In addition, two different sensitivity analyses were also carried out. The sensitivity analysis on the criteria weights revealed that the alternatives were highly influenced by these weights. Based on these results, it can be concluded that this study offers a practical framework for countries to select the appropriate UCAV and makes a significant contribution to the literature in this field.

Conceptual Design of a Low-Cost Class-III Turbofan-Based UCAV Loyal Wingman

The rapid evolution of military technology has led to an increased interest in Unmanned Combat Aerial Vehicles (UCAVs). This research focuses on the conceptual design of a low-cost, turbofan-powered UCAV, specifically a Class-III aircraft as defined by NATO classification (STANAG 4670), with a target take-off weight of approximately one tonne. The study adopts a “from scratch” design approach, recognizing the limitations of existing data and the potential for scaling errors. This approach involves a meticulous design process that includes the development of precise requirements, weight estimations, and iterative optimization of the aircraft layout to ensure aerodynamic efficiency and operational functionality. A key element of this conceptual design is its focus on a low-cost profile, achieved through the adoption of a simplified structural layout, and the integration of off-the-shelf components where possible. The design process involves an iterative approach, beginning with fundamental requirements and progressing through the detailed development of individual components and their integration into a cohesive aircraft. The study details the selection of an existing and operational engine due to its power output. The design and analysis of the wing, fuselage, and V-tail configuration are presented, incorporating considerations for aerodynamic efficiency, stability, weight estimation, and internal component layout. The study concludes by outlining recommendations for future work, including high-fidelity CFD simulations, structural analysis, and the integration of advanced electronic systems and AI capabilities essential for the Loyal Wingman concept.

REDEFINISI PRINSIP PEMBEDAAN DALAM HUKUM HUMANITER INTERNASIONAL DI ERA PERANG DRONE: STUDI KASUS GAZA DAN UKRAINA

The development of combat drone technology has revolutionized the landscape of modern warfare, but also presents new challenges to the fundamental principles of International Humanitarian Law (IHL), particularly the principle of distinction between combatants and civilians. This article examines the ethical and legal dilemmas of drone usage through a qualitative normative juridical approach, using case studies from the Gaza conflict (Israel vs. Hamas) and the Russia–Ukraine war. The analysis reveals that despite drones offering high precision, field practices often demonstrate violations of the principle of distinction, whether due to intelligence negligence or policies that relax the definition of combatants. The technological imbalance of drone warfare also risks eroding humanitarian values and dehumanizing victims. This study underscores that technological advancement must be accompanied by the strengthening of legal accountability, the integration of ethics into military procedures, and the adaptation of operational rules to uphold humanitarian principles in warfare. Therefore, redefining the application of the principle of distinction is necessary to address the challenges of remote drone-based warfare, in order to ensure that the value of life remains protected amidst the escalation of military technology

Maghreb Power Struggle: An Offensive Realist Analysis of Moroccan-Algerian Rivalry

This paper analyzes the long-standing conflict between Morocco and Algeria in the Maghreb region using John Mearsheimer's offensive realism theory. Through the evaluation of historical enmities, the conflict over Western Sahara, and rivaling geopolitical blocs, this study illustrates the self-help nature of the international order that rewards the adoption of aggressive policies such as militarization, hybrid conflict, and alignment with global powers. The methodology integrates discourse analysis of elite narratives and escalation pathways with comparative case studies, such as Morocco’s normalization with Israel in the 2020 Abraham Accords and Algeria’s military agreement with Russia in 2023, alongside the analysis of the narratives accompanying the escalation. Both states seek to justify hegemonic behaviors by application of offensive realism arguments, such as survival in an anarchical system, a lack of trust regarding the intentions of adversaries, and the need to gain power more than what is required. Morocco acquiring asymmetric Israeli military drones and USA defense partnerships, along with Algeria’s Russian Su-57 jets and cyberwarfare investment arms race is a spiral of security dilemma proliferation through external sponsor enablement. With Algeria utilizing the Polisario Front to limit Moroccan influence, Morocco strategically frames the Western Sahara conflict as essential for maintaining national integrity leading to Morocco-Algeria territorial conflict polarization in the region. These phenomena led to Morocco-Algeria stunted integration through the immobilized energy politics of the Arab Maghreb Union, bifid energy diplomacy of green hydrogen partnerships led by Morocco versus gas siphoning geopolitics of Algeria, and proxy wars in the Sahel region. This transforms the Maghreb region into a bipolar security complex with increased chances of open conflict, driven by NATO encroachment through Morocco and Russian encroachment via Algeria, this study identifies as an outcome of NATO and Russian intrusion in North Africa. Using the lens of regional security complex theory in conjunction with offensive realism, this research sought to analyze how rivalries between middle powers impact outer peripheries of the geostrategic world in the context of multipolar competition. Proposals focused on the EU-mediated energy collaboration, African Union cyber stability initiatives, and other measures aimed at escalation reduction are provided alongside the findings.

Analysis of the basic aerodynamic characteristics of an unmanned combat aerial vehicle based on a CAD model

Analysis of the basic aerodynamic characteristics of an unmanned combat aerial vehicle based on a CAD model

Hierarchical Reinforcement Learning with Automatic Curriculum Generation for Unmanned Combat Aerial Vehicle Tactical Decision-Making in Autonomous Air Combat

This study proposes an unmanned combat aerial vehicle (UCAV)-oriented hierarchical reinforcement learning framework to address the temporal abstraction challenge in autonomous within-visual-range air combat (WVRAC) for UCAVs. The incorporation of maximum-entropy objectives within the MEOL framework facilitates the optimization of both autonomous low-level tactical discovery and high-level option selection. At the low level, three tactical policies (angle, snapshot, and energy tactics) are designed with reward functions informed by expert knowledge, while the high-level policy dynamically terminates current tactics and selects new ones through sparse reward learning, thus overcoming the limitations of fixed-duration tactical execution. Furthermore, a novel automatic curriculum generation mechanism based on Wasserstein Generative Adversarial Networks (WGANs) is introduced to enhance training efficiency and adaptability to diverse initial combat conditions. Extensive experiments conducted in UCAV air combat simulations have shown that MEOL not only achieves significantly better win rates than other policies when training against rule-based opponents, but also that MEOC achieves superior results in tests against tactical intra-option policies as well as other option learning policies. The framework facilitates dynamic termination and switching of tactics, thereby addressing the limitations of fixed-duration hierarchical methods. Ablation studies confirm the effectiveness of WGAN-based curricula in accelerating policy convergence. Additionally, the visual analysis of UCAVs’ flight logs validates the learned hierarchical decision-making process, showcasing the interplay between tactical selection and manoeuvring execution. This research provides novel methodologies combining hierarchical reinforcement learning with tactical domain knowledge for the autonomous decision-making of UCAVs in complex air combat scenarios.

AI And Military Precision In Drones Attack On The Israeli-Hamas Conflict

This paper investigated the nexus between AI and military precision in drone attacks on the Israeli-Hamas conflict to proffer a research-based strategy for regulating the AI-enabled weapon systems, likewise addressing a way forward to peace and conflict resolution. Anchored on a three-stream ambit of the 'Just War' theory, the 'Technological Determinism' theory, and the 'Security Dilemma' theory, efforts were made to integrate these distinct perspectives to analyze the complexity of AI on military operations, including the ethical implications and strategic outcomes for the Israeli-Hamas conflict. Findings revealed that AI is reshaping the landscape of military operations in the Israeli-Hamas conflict, mainly through its application in drone strikes. Regarding military precision, AI technologies enable sophisticated data analyses that facilitate enhanced targeting and surveillance capabilities. However, the integration of AI in drone warfare poses serious challenges in international law and military ethics since the precision of AI-driven strikes does not eliminate the risk of civilian casualties, raising contestation about the moral justifications for their use in densely populated areas, like what happened in Gaza. This paper states that the future of AI and military drone precision in the Israeli-Hamas conflict requires a careful balance between technological advancements and ethical considerations. By prioritizing human oversight, accountability, and humanitarian principles, stakeholders can harness the benefits of AI while mitigating risks associated with its use in warfare. Such a multifaceted approach is essential for fostering responsible military engagement and enhancing the prospects for peace. The paper recommended emergency protocols that allow for the reevaluation of drone targeting decisions in real-time to help prevent unintended harm, especially in such rapidly changing conflict environments as the Israeli-Hamas conflict. But most importantly, there is a need to address the root causes of this Israeli-Hamas conflict. While the path to peace in this conflict is fraught with challenges, sustained commitment from local and international actors is essential to foster a durable resolution.

Aplicaciones de la Inteligencia Artificial en vehículos aéreos no tripulados

This article examines the applications and benefits of artificial intelligence (AI) in military drones, highlighting how this technology has revolutionized their capabilities. AI enables drones to perform more autonomous operations, improve data analysis, and optimize decision-making, reducing human error and increasing effectiveness and efficiency in reconnaissance, surveillance, and combat missions. It also uses it to prevent and respond to dangerous emergencies such as the El Niño phenomenon or forest fires, in which the Armed Forces play a constitutional role, as well as in citizen security. International examples are presented, such as the development and use of AI-powered drones in the United States, China, and France, which are at the forefront of integrating this technology into their Armed Forces. The article also discusses the implications of this integration of AI into military drones, emphasizing the challenges faced by countries that do not develop these capabilities, creating a technological gap that could compromise their security. Modernizing the Armed Forces and training specialized personnel are critical to making the most of emerging technologies, ensuring effective and strategic integration of AI into national defense.

Hierarchical La-doped Bi₂Fe₄O₉/polypyrrole heterostructures with truncated pyramid nanostructure: A novel design for enhanced electromagnetic wave absorption

This paper presents a novel design for electromagnetic wave (EMW) absorbing materials, focusing on a composite heterostructure of La-doped Bi2Fe4O9 (BLFO) and polypyrrole (PPy) with a truncated pyramid nanostructure. This research aims to overcome the limitations of traditional EMW absorbers by leveraging the unique nano-morphology and properties of the BLFO@PPy composite. The unique microstructure of BLFO endows the composite with abundant interface polarization, while PPy significantly enhances the conduction loss. The resulting synergistic effect substantially improves the EMW absorption performance. The study demonstrates that La doping in Bi2Fe4O9 leads to the formation of a truncated pyramid nanosheet array. When combined with PPy, this structure significantly enhances interface polarization, scattering, and absorption of EMWs. Specifically, the sample BLFO@PPy-3 exhibits superior EMW absorption performance, achieving a minimum reflection loss (RLmin) of − 64.20 dB and an effective absorption bandwidth (EAB) of 7.20 GHz. The effectiveness of this design is validated through comprehensive electromagnetic simulations. The simulation of the radar cross-section (RCS) indicates that BLFO@PPy-3 significantly enhances the stealth performance of unmanned combat aerial vehicles (UCAVs). Furthermore, the paper investigates the thermal conductivity properties of the composite, highlighting its potential for thermal management alongside EMW absorption. By optimizing the PPy content, the thermal properties of the composite can be precisely controlled, ensuring stable performance in practical applications. These findings offer valuable insights into the design and development of next-generation multifunctional EMW absorbing materials for diverse military and industrial applications.

Experimenting with Drones: Remotely Piloted Aircraft and Security Practices in Brazil

Abstract In the past decades, remotely piloted aircraft systems, hereby referred to as military drones, have grown as a literature topic across disciplines. However, most of the debate has focused on contexts concerning major powers conducting counterterrorism and counterinsurgency campaigns, or how drones may or not impact interstate conflicts. To emphasize that security technologies and weapons circulate and reach contexts distinctly on global and local levels, this paper analyses how drone technology has been assimilated in Brazil. Focusing on the Air Force experience from 2008 onwards, we draw from critical security studies’ mapping approach to understand different aspects concerning the process of implementing drones in the country and its effects on local practices: how they circulate on the global market, how they are de facto deployed in operations, and how they are depicted in the organization’s knowledge and expectations. We resort to different primary sources including doctrines, field manuals, military school papers, and a survey with Air Force officials. We argue that this process can be seen as experimentation, characterized by an epistemic violence embedded in drones’ design and the logic of target definition, and local sociological features of Brazil’s military ethos concerning technological imaginaries. Beyond broader processes of prototype warfare and testing at the global level, we focus on how the local forces experiment with the artifact while building their self-image and reproducing security practices that reinforce a population-centered violence.

Autonomous Maneuver Decision-Making for Unmanned Combat Aerial Vehicle Based on Modified Marine Predator Algorithm and Fuzzy Inference

In recent years, autonomous maneuver decision-making has emerged as a key technology in autonomous air combat confrontation, garnering widespread attention. A method combining the modified marine predator algorithm (MMPA) and fuzzy inference is proposed to solve the autonomous maneuver decision-making problem of an unmanned combat aerial vehicle (UCAV). By incorporating the missile attack strategy into the process of calculating the maneuver strategy, the air combat decision-making capability of the UCAV is enhanced. First, the weight coefficients determined by the fuzzy inference method are combined with air combat superiority functions that consider the current missile attack zone and then the objective function is obtained, which is to be optimized at the current moment. Second, the MMPA is used to solve the objective function to obtain the missile attack maneuver strategy and the maneuver strategy for defending against missile attacks. A comparative analysis with other classical intelligent optimization algorithms highlights the advantages of the proposed method. Furthermore, the air combat confrontation simulation experiments are conducted under six different initial scenarios, namely, neutral, offensive, oppositional, defensive, parallel, and head-on. The simulation results show that the integrated maneuver and missile attack decision-making capabilities of the UCAV are improved using the proposed autonomous maneuver decision-making method.

The new Turbo Wing – TW propulsion for VTOL aircraft

This paper relates about to a new class of propulsion systems named Turbo Wing- TW for VTOL aircraft (including civil and military drones). The idea behind this concept is to fully integrate a propulsion system into a wing structure, so that the aircraft takes full benefits of the coupling of wing aerodynamics and the propulsion thrust stream.

Independent Soft Actor‐Critic Deep Reinforcement Learning for UAV Cooperative Air Combat Maneuvering Decision‐Making

ABSTRACTThis paper delves into the research of collaborative combat strategies for multiple unmanned combat aerial vehicles (UAVs), utilizing the independent soft Actor‐Critic (is‐AC) algorithm. We aim to achieve collaborative jamming confrontation, accurate battlefield situational awareness, and UAV decision‐making capabilities to control their behavior. However, the SAC algorithm is plagued by instability and poor scalability in Multi‐agent reinforcement learning scenarios. To address this, we draw inspiration from the Independent Q‐Learning (IQL) algorithm and improve SAC. Our experimental analysis of the is‐AC algorithm in UAV confrontation models demonstrates its stability and scalability in multi‐machine scenarios.

Research on the Issue of CBRN Drone Attacks in Island Control and Stability Maintenance Operations of the Armed Police Force

With the rapid development of military drone technology, its widespread application in military and civilian fields has introduced new security challenges. In particular, the potential threats posed by drones during mission execution present risks to public safety and social stability. This paper aims to explore the potential impact of CBRN (Chemical, Biological, Radiological, and Nuclear) drones on control and stability maintenance operations and corresponding countermeasures. By analyzing the advantages of drones in terms of low cost, high efficiency, and flexibility, this paper examines how drones can serve as effective operational tools and proposes targeted prevention and emergency response measures. The research indicates that drones can swiftly and covertly deliver hazardous substances, posing significant security risks, especially in controlled environments with high population density. The paper suggests establishing a comprehensive counter-drone system, optimizing early warning and defense measures, and strengthening emergency response capabilities to effectively address related threats.

Tactical Coordination-Based Decision Making for Unmanned Combat Aerial Vehicles Maneuvering in Within-Visual-Range Air Combat

Targeting the autonomous decision-making problem of unmanned combat aerial vehicles (UCAVs) in a two-versus-one (2v1) within-visual-range (WVR) air combat scenario, this paper proposes a maneuver decision-making method based on tactical coordination. First, a coordinated situation assessment model is designed, which subdivides the air combat situation into optimization-driven and tactical coordinated situations. The former combines missile attack zone calculation and trajectory prediction to optimize the control quantity of a single aircraft, while the latter uses fuzzy logic to analyze the overall situation of the three aircraft to drive tactical selection. Second, a decision-making model based on a hierarchical expert system is constructed, establishing a hierarchical decision-making framework with a UCAV-coordinated combat knowledge base. The coordinated situation assessment results are used to match corresponding tactics and maneuver control quantities. Finally, an improved particle swarm optimization algorithm (I-PSO) is proposed, which enhances the optimization ability and real-time performance through the design of local social factor iterative components and adaptive adjustment of inertia weights. Air combat simulations in four different scenarios verify the effectiveness and superiority of the proposed decision-making method. The results show that the method can achieve autonomous decision making in dynamic air combat. Compared with decision-making methods based on optimization algorithms and differential games, the win rate is increased by about 17% and 18%, respectively, and the single-step decision-making time is less than 0.02 s, demonstrating high real-time performance and win rate. This research provides new ideas and methods for the autonomous decision making of UCAVs in complex air combat scenarios.