UCAV Research Articles

Hierarchical Decision-Making Framework for Multiple UCAVs Autonomous Confrontation

Autonomous decision-making for air confrontation between unmanned combat aerial vehicles remains hard to be designed due to dynamic situations and complex interactions. Rule-based decision-making methods provide a powerful solution with better interpretability. However, various hand-crafted rules may result in conflicts and poor scalability issues. To overcome this problem, this work proposes a hierarchical decision-making framework called State-Event-Condition-Action (SECA), which integrates the finite state machine and event-condition-action frameworks. This framework provides three products for system design: the SECA model–an abstract model of rules; the SECA state chart–a graphical visualization of rules; and the SECA rule description–a machine-readable format for practical deployment. The SECA framework offers several advantages, including convenient deployment, high efficiency, better logicality, and scalability. Simulation results demonstrate that the SECA framework enables autonomous decision-making in air confrontation scenarios and outperforms the event-condition-action framework in terms of computational time and cost-effectiveness. Furthermore, the generalization test in robot navigation tasks verifies its potential applicability to other domains with different background knowledge.

Military Efforts to Liberate Karabakh

Diplomacy plays an invaluable role during war to bring belligerents on favorable terms. It helps statesmen to open channels of communications with a range of actors e.g., allies, foe and neutral states to prevent them from becoming a party. Armenia illegally occupied twenty percent of Azerbaijan’s sovereign territory. It used track I diplomacy for delaying tactics, blatantly refused to withdraw occupation forces despite United Nations Security Council (UNSC) resolutions. Yet, Baku did not lose faith in the multilateral approach. It anticipated and endeavored to resolve the Karabakh conflict in the light of policy based on war avoidance. This paper using qualitative research method highlights and analyses available literature on President Ilham Aliyev’s role in achieving Azerbaijan’s national objective during the war and in the post-war era. After coming to power President Ilham Aliyev decided to regain military strength and introduced a military modernization process. In pursuit to achieve this objective presidential office paid special attention to acquire dual use medium-altitude unmanned aerial vehicles (UAVs), long-endurance Hermes-900 surveillance drones, and Heron; loitering munitions such as SkyStriker, Harop and Orbiter 1K, and Bayraktar TB2 unmanned combat aerial vehicles. Beside military modernization, President of zerbaijan was active at diplomatic front to prevent Armenian allies from entering war against Azerbaijan. Combination of politico-military efforts paved the way to force the enemy to withdraw occupation forces. Conversely, lost pride and glory was returned to the masses of Azerbaijan. The second task authors believe performed by President Ilham is to highlight enemy war crimes. In conclusion, victory in 44 Days war was ensured because leadership and the masses were on the same page

Znanja, veštine i sposobnosti neophodni za operatere UAS

The use of combat and commercial drones is on the rise. In addition to the use of military drones for military purposes and commercial drones for civilian purposes, the recent conflicts in Nagorno-Karabakh and Ukraine also indicated the possibility of using commercial drones for military purposes. The profession of drone operator is becoming increasingly popular among young people interested in STEM education. Different tasks and activities require somewhat different drone operator skills, but the basics are the same. The aim of this paper is to analyze the knowledge, skills and abilities for UAS operators, both military and civilian. Based on the analysis of the literature and the results of the focus group discussion, the job descriptions were created with the job specifications for military and civilian UAS operators, along with recommendations for the future development of UAS operators in the Republic of Serbia.

Nove perspektive u pogledu borbene upotrebe komercijalnih dronova u kontekstu rusko-ukrajinskog sukoba

The use of combat drones is gaining momentum. In recent years, the phenomenon of the use of commercial drones for the realization of military tasks increased signifificance. The aim of this paper is to provide an answer to the possible directions of further use of this technology, as well as to the effects and dimensions of the existing application, by analyzing the current military conflict in Ukraine as a lesson for the defence system of the Republic of Serbia. Possible dimensions of the application of commercial drones in local conflicts are analyzed through a situational SWOT analysis. The derived conclusion provides a realistic picture of the position reached through the analysis and gives a view of dimension of its use from two opposite angles.

Obtaining of the Modal Frequency Parameters a Middle Class Armed Unmanned Combat Aerial Vehicle Using Engineering Simulation ANSYS Program

Baykar Bayraktar TB2 (Tactical Block 2) is a domestically armed unmanned aerial vehicle produced by Turkey-based Baykar Defense. It is accepted in the middle class armed unmanned aerial vehicle class with its dimensions and the amount of useful load it can carry. Medium UAV class is an accepted classification for UAV’s that are too heavy to be carried by one person but still smaller than a light aircraft. There are also medium-sized UAV’s with a rotary base. Unmanned combat aerial vehicle (UCAV), also known as fighter aircraft, colloquially abbreviated as drone, is an unmanned aerial vehicle (UAV) used for intelligence, surveillance, target designation and reconnaissance and carrying aircraft munitions. Drones can use missiles, ATGM’s and/or bombs at fixed points for their attacks. Drones are often under real-time human control and have varying degrees of autonomy. Unlike unmanned surveillance and reconnaissance aircraft, SİHAs are used for both unmanned aerial vehicle attacks and battlefield intelligence. The solid model was used ready-made in 1:1 scale. All the parameters were obtained using the Rotax 912 engine with two blades used in the design of the primary models. Modal analysis is that the study of dynamic properties of systems below vibration. Accelerometers help calculate the vibration of the system when attached to a shaker. Modal analysis on aircraft emerges as the analysis of the vibration period and modes of the wind on aircraft. Analyzing the solid model according to the correct design criteria in the analysis program, making the correct simplifications, getting the mesh network properly and with success, directly have an affect on the accuracy of the modal analysis results.

A multi-population immune plasma algorithm for path planning of unmanned combat aerial vehicle

Autonomous flight of an unmanned aerial vehicle (UAV) or its weaponized variant named unmanned combat aerial vehicle (UCAV) requires a route or path determined carefully by considering the optimization objectives about the enemy threats and fuel consumption of the system being operated. Immune Plasma algorithm (IP algorithm or IPA) is one of the most recent optimization techniques and directly models the fundamental steps of a medical method also used for the COVID-19 disease and known as convalescent or immune plasma treatment. In this study, IP algorithm for which a promising performance has already been validated with a single population was first extended to a multi-population domain supported by a migration schema. Moreover, the usage of the donor as a source of plasma for the treatment operations of a receiver was remodeled. The new variant of the IPA empowered with the multi-population and modified donor usage approach was called Multi-IP algorithm or MULIPA. For investigating the solving capabilities of the MULIPA as a UCAV path planner, different battlefield scenarios and algorithm specific parameter configurations were used. The results obtained by the MULIPA were compared with the results of other meta-heuristic based path planners. The comparative studies between MULIPA and other techniques showed that newly proposed IPA variant is capable of finding more secure and fuel efficient paths for a UCAV system.

On naming drones: a European perspective

This article discusses the naming of military drone technology by different actors. It thus explores the tension between producing, using, and experiencing drone technology. I will look at, among other things, the project of a drone called the Euro Hawk while reflecting on the experiences and perceptions of people from “outside” Europe. For my investigation, I used three types of journalistic texts in Arabic: (1) texts produced by professional platforms that are financed by European governments like Deutsche Welle and Qantara.de, (2) texts published on the news platform Aljazeera.net and (3) entries at the popular online encyclopedia Wikipedia.

Air Combat Maneuver Decision Method Based on A3C Deep Reinforcement Learning

To solve the maneuvering decision problem in air combat of unmanned combat aircraft vehicles (UCAVs), in this paper, an autonomous maneuver decision method is proposed for a UCAV based on deep reinforcement learning. Firstly, the UCAV flight maneuver model and maneuver library of both opposing sides are established. Then, considering the different state transition effects of various actions when the pitch angles of the UCAVs are different, the 10 state variables including the pitch angle, are taken as the state space. Combined with the air combat situation threat assessment index model, a two-layer reward mechanism combining internal reward and sparse reward is designed as the evaluation basis of reinforcement learning. Then, the neural network model of the full connection layer is built according to an Asynchronous Advantage Actor–Critic (A3C) algorithm. In the way of multi-threading, our UCAV keeps interactively learning with the environment to train the model and gradually learns the optimal air combat maneuver countermeasure strategy, and guides our UCAV to conduct action selection. The algorithm reduces the correlation between samples through multi-threading asynchronous learning. Finally, the effectiveness and feasibility of the method are verified in three different air combat scenarios.

Multi-UCAV Cooperative Target Allocation Based on Energy-Reserved Chemical Reaction Algorithm (CNCRO)

Aimed at the disadvantages of constrained processing technology in the cooperative target allocation of multiple unmanned combat aircraft (UCAV), the energy-reserved chemical reaction algorithm (CNCRO) is proposed to solve the constrained optimization problems. On the one hand, convert multiple constraint conditions of the multi-UCAV target allocation into optimization targets to transform the constrained processing problem into a multiobjective optimization problem including allocation goals and constrained optimization goals. On the other hand, the energy-reserved chemical reaction algorithm (CNCRO) is proposed, which introduces the environmental energy-reserved variables buffer into the ineffective collision, combination or splitting reactions between single molecule and multimolecules of CNCRO, which is used to boost energy for the low kinetic energy molecules, so as to reduce its kinetic energy in case of invalid collision of molecules and control it to gradually stabilize and converge. At the same time, the splitting reaction is inspired, to greatly change the structure of molecules, promote its search for more solution space, and improve the splitting reaction ability and its global optimization ability. Finally, the simulation experiment is completed by using MATLAB software. The advantages of CNCRO in accuracy are verified by 8 standard test functions, the influence of the weight coefficients in the cooperative target allocation function of UCAV is studied, which are revenue, loss, and voyage, and the target allocation schemes of traditional constrained processing and unconstrained multiobjective optimization methods based on different attack target number C i and total target number N are investigated, to obtain the control law, which can be used to guide the given parameters with different emphases.

Network Security Analysis Simulation at the GCS in the UCAV to support the Indonesian Defense Area

An unmanned Combat Aerial Vehicle (UCAV) is an unmanned aircraft that has a serial control communication device that can be seen directly in real-time. In carrying out UCAV flights, it requires good and stable data transmission security so that signal loss does not occur during the communication process. Researchers create a concept of a security scheme in communication at the Ground Control Station (GCS) that can be used for the use of UCAV communication at long distances, using the Quality of Service (QoS) method from OPEN VPN with parameters Throughput, Packet Loss, Delay (Latency) and Jitter can determine the reliability of a UCAV communication network. Based on the results of Quality of Service (QoS) testing with OpenVPN Autopilot UCAV objects on the ICMP protocol have the smallest packet loss value of 0%, the delay parameter is 5.2ms, the jitter parameter gets a high value of 4.68 ms higher than the TCP protocol and UDP. The TCP protocol has a relatively small packet loss value of 0.3% and ranks second to the ICMP protocol, then the delay value is 8.48 ms greater than the ICMP and UDP protocols, and the jitter parameter value is 0.0013 ms smaller than the ICMP and UDP protocols. The use of VPN OVPN is a good recommendation. Still, researchers suggest that should use not only OPEN VPN but also L2TP VPN and PPTP VPN for security at the Ground Control Station at UCAV as a comparison.

ANALISA AERODINAMIK, STRUKTUR, FLIGHT DYNAMIC AND PERFORMANSI UCAV (UNMANNED COMBAT AIR VEHICLE)

PTTA (Unmanned Aircraft) is also used to support national security and reconnaissance, making it easier for the TNI to work and simultaneously saving the cost of monitoring Indonesian territories. This study will produce design details, design analysis with design configuration requirements from UCAV (Unmanned Combat Air Vehicle), which has Weight and Balance with a two-point landing case so that UCAV is declared safe to receive maximum load loads and flutter analysis shows that the vehicle does not occur. Flutter phenomenon up to a speed of 150 KTAS meets the requirements of aeroelastic flutter based on the rules set by CASR (Civil Aviation Safety Regulations) 23 and IMA (Indonesian Military Airworthiness). From the identification of DR&O (Design Requirements and Objectives) and Initial Sizing, there is an effect of airflow and angle of attack on UCAV on aerodynamic characteristics, used as contours of pressure and temperature on the body and vector for UCAV body velocity. Pressure contours, temperature contours, and velocity vectors on the UCAV so that the analysis in determining the performance of the aircraft is representative following CASR regulations 23 and 24

Autonomous maneuver decision-making method based on reinforcement learning and Monte Carlo tree search

Autonomous maneuver decision-making methods for air combat often rely on human knowledge, such as advantage functions, objective functions, or dense rewards in reinforcement learning, which limits the decision-making ability of unmanned combat aerial vehicle to the scope of human experience and result in slow progress in maneuver decision-making. Therefore, a maneuver decision-making method based on deep reinforcement learning and Monte Carlo tree search is proposed to investigate whether it is feasible for maneuver decision-making without human knowledge or advantage function. To this end, Monte Carlo tree search in continuous action space is proposed and neural networks-guided Monte Carlo tree search with self-play is utilized to improve the ability of air combat agents. It starts from random behaviors and generates samples consisting of states, actions, and results of air combat through self-play without using human knowledge. These samples are used to train the neural network, and the neural network with a greater winning rate is selected by simulations. Then, repeat the above process to gradually improve the maneuver decision-making ability. Simulations are conducted to verify the effectiveness of the proposed method, and the kinematic model of the missile is used in simulations instead of the missile engagement zone to test whether the maneuver decision-making method is effective or not. The simulation results of the fixed initial state and random initial state show that the proposed method is efficient and can meet the real-time requirement.

Path Following for Unmanned Combat Aerial Vehicles Using Three-Dimensional Nonlinear Guidance

An effective path-following guidance algorithm for unmanned combat aerial vehicles by pursuing a look-ahead target-point along the desired path is devised. The concept of look-ahead pursuit for 3-D path-following was extended from the planar <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\mathcal {L}_1}$</tex-math></inline-formula> guidance, which has been widely adopted in the application of lateral guidance of fixed-wing drone. Decoupled implementation of the planar guidance action on each of the longitudinal (vertical) and lateral (horizontal) planes supplies longitudinal-lateral acceleration commands in two perpendicular planes which is well accepted by aviation engineers. The computation of the look-ahead point utilizes a finite and iterative numerical search method by introducing an auxiliary path-related parameter. Furthermore, additional implementation-specific details such as the modification of adaptive <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\mathcal {L}_1}$</tex-math></inline-formula> length and the protection strategies ensuring wide applicability of the algorithm indeed guarantee certain necessity to be considered in real implementation of the guidance law. The improved schemes eliminate complicated coordinate transformations and are built on the path-independent assumption, thus making them easier to be adjusted between various types of paths, including discrete optimal trajectories. Monte Carlo simulations and real-world flight tests have confirmed the effectiveness of the nonlinear guidance algorithm.

A Multi-UCAV Cooperative Decision-Making Method Based on an MAPPO Algorithm for Beyond-Visual-Range Air Combat

To solve the problems of autonomous decision making and the cooperative operation of multiple unmanned combat aerial vehicles (UCAVs) in beyond-visual-range air combat, this paper proposes an air combat decision-making method that is based on a multi-agent proximal policy optimization (MAPPO) algorithm. Firstly, the model of the unmanned combat aircraft is established on the simulation platform, and the corresponding maneuver library is designed. In order to simulate the real beyond-visual-range air combat, the missile attack area model is established, and the probability of damage occurring is given according to both the enemy and us. Secondly, to overcome the sparse return problem of traditional reinforcement learning, according to the angle, speed, altitude, distance of the unmanned combat aircraft, and the damage of the missile attack area, this paper designs a comprehensive reward function. Finally, the idea of centralized training and distributed implementation is adopted to improve the decision-making ability of the unmanned combat aircraft and improve the training efficiency of the algorithm. The simulation results show that this algorithm can carry out a multi-aircraft air combat confrontation drill, form new tactical decisions in the drill process, and provide new ideas for multi-UCAV air combat.

An Investigation into Trevor Paglen’s Drones Photographs, Military Targeting, and Looking Slowly

The technology of unilateral remote warfare develops continuously, and with it, an ever-rising threat to human lives and freedom from an array of actors, mostly state powers, that seek to use oppressive force against civilian populations. Trevor Paglen is a political visual artist, whose project Drones represents military operations and resources in ways that recontextualize the processes of visual targeting enacted by military drones. Paglen’s work highlights the differences between human and machine vision and creates deliberate obfuscation that renders his photographs visually abstract. Following work by TJ Clark, Ariella Azoulay and Arden Reed, I approach Paglen’s photograph Untitled (Reaper Drone) in the form of a slow investigation that highlights durational viewing. Slowness in this form creates a conversation between myself and the image that acknowledges the temporal dimension of art-viewing and resists the unilateral gaze of the drone.

The Art of Drone Warfare

The increasing prevalence of drone strikes, and the expanding applications of drones in different industries, are dissolving the boundaries between military and civilian realms. This special issue considers 'the art of drone warfare' by surveying the field of scholarship on drone warfare and drone art to date. It addresses the affective, discursive, technopolitical, and colonial histories underpinning drone systems, through essays discussing various cultural works encompassing marketing video, film, literature, and the visual arts. Despite the unresolved controversies surrounding the ethics of remote warfare, military drone use has become normalised. Examining the art and aesthetics of drone warfare helps to make its politics perceptible at a time when the logic behind autonomous military systems is becoming entrenched.

A double-layer coding model with a rotation-based particle swarm algorithm for unmanned combat aerial vehicle path planning

Unmanned combat aerial vehicle (UCAV) technology has to address many challenges in complex battlefield environments. To produce a safe and low-energy flying path, a UCAV requires many points to build a path that avoids threats, which increases the problem dimension, consumes more computational resources and makes the results unstable. To address this issue, this paper employs a new model known as double-layer coding (DLC) for path planning with unevenly distributed points to decrease the number of superfluous points on the path. Meanwhile, the RPSO algorithm, which introduces a novel strategy of rotating particles in high-dimensional space to search for targets, is proposed as an enhanced particle swarm optimization (PSO) algorithm. The proposed method effectively improves PSO′s exploration capacity. Furthermore, RPSO is employed to implement the double-layer coding model for path planning (DLCRPSO). The experimental results show that the proposed DLCRPSO method for path planning always produces feasible flight paths in complex environments.

Optimization Design of Multi-UAV Communication Network Based on Reinforcement Learning

In recent years, due to the application of high-definition video codec technology, high-precision satellite navigation technology, mobile base station positioning technology, and broadband technology, the performance of UAVs has been greatly improved. In the military field, drones have become an important weapon alongside missiles on the battlefield. In the future, military drones will perform strategic missions such as battlefield reconnaissance and long-range destruction. Outside the military field, DJI’s Zenmuse series drones are used for filming, MG series drones are used for pesticide spraying, and Beijing Zhonghangzhi unmanned helicopters are used for geological surveys, precise inspection of power lines, and maritime law enforcement. With the continuous improvement of technical specifications, UAV communication technology requires further research and development. This paper has conducted research experiments on the optimization of multi-UAV communication network based on reinforcement learning. The experimental data show that it is marked as the AoI value corresponding to the completion of a certain self-task. It can be seen that the final AoI of the communication trajectory of reinforcement learning is 115, and the AoI greedy strategy finally obtains AoI of 140 seconds, achieving about 18% of the total AoI reduce, which effectively improve the performance of the system. From the above data, the research of reinforcement learning method has great benefits for the development of UAV communication.

Drone trauma: violent mediation and remote warfare

For people subject to drone war in Gaza, Pakistan, Yemen and elsewhere, the violence and trauma inflicted by remotely piloted aerial systems such as the MQ-9 Reaper takes place at a remove from the sensors, networks, algorithms and interfaces that launch Hellfire and other missiles from the air. Brutal death and wounding bely the precision rhetoric, technocratic discourses and technoscientific imaginaries that shroud drone warfare in popular and political debate over its merits. Much has been said about the traumas of drone operators, but less about the traumas produced by drone warfare in those individuals and communities subject to it. In this short article, I pursue the question of how those traumas on the ground are bound up with the media-technological entities, processes and affects that compose the military drone apparatus: sensors, networks, algorithms, interfaces, atmospheres and missiles. My core contention is that the trauma of drone warfare is characterised by the violent mediation of drone systems, which produce an intensive relation between the not-yet of traumatic violence having commenced before it is felt and the already-too-late of that experience.

한국형 위성항법시스템(KPS)을 활용한 군사용 드론의 위치추적 및 회수 방안

Drones are emerging as a primary means rather than a secondary ones to wage war around the world. For this reason, military drones are concentrated in a country’s science and technology, and if they are crash-landed or are seized and fall into the hands of hostile forces, it can be fatal to national security. The Republic of Korea (ROK) armed forces are no exception as it is spurring the deployment of drones while advocating for advanced science and technology forces. Just in time, the Ministry of Science and ICT is promoting the Korean Satellite Navigation System (KPS) project that provides search and rescue services. Therefore, if the ROK armed forces establish a location tracking and recovery system for military drones using KPS in consultation with the Ministry of Science and ICT, it will be possible to stably operate military drones. Through this, the ROK armed forces is able to protect military science and technology in time of emergency.