Actual Battlefield Research Articles

INFORMATION WARFARE IN TERMS OF COMMUNICATION THEORY: ATTEMPTED ANALYSIS

The modern information age brings changes to all phenomena of human life. For example, the natu re of wars change. They are transferred from the actual battlefield to the information space, i.e. they become hybrid. The winner is the one whose narrative becomes dominant in the global information space. The Russian-Ukrainian war is a vivid example of the latest confrontation. It takes place between two absolutely opposite positions, a compromise between which is impossible. This conflict is deeply existential, because Russia sharply denies the existence of Ukraine as an independent state and as a nation in general. This is evidenced by the rhetoric of the aggressor state and numerous war crimes. However, this war is not only between two sides. By denying Ukraine its existence, Russia is also at war with the values that Ukrainians uphold and on the basis of which they strive to build their own country. And these are the values of the free democratic world. Therefore, Russia opposes not only one country, but all those who also share them. That is why the information war begins to reach far beyond the borders of Ukraine. Already today, we can see the influence of Russia, whose propaganda influences the agenda of many leading Western countries. Using both classic mass media (newspapers, radio, television) and new ones (communities in social networks, bloggers, etc.), it intervenes in the global information space. The Internet only further complicates the dissemination of reliable information and promotes propaganda, because now there is almost no control over the flow of information. Habermas states this problem, noting that everyone is now a potential author without editorial control. Therefore, in conditions where the mass media gravitate towards entertainment and most of the information flows in an uncontrolled stream, there is a war for human minds. That’s why the current situation becomes a challenge for communicative theory, which has learned to make a correct diagnosis, but has not yet offered its option for exiting the crisis. Habermas’ post “War and In dignation” is so far only a testimony to the failure of his philosophy in the face of real challenges. Therefore, modern war is also a direct test for communicative theory, which must either find a way out of its limits or confirm its defeat.

Impact of Soil on the Penetration of Prefabricated Spherical Fragments and Its Protective Effect

As a natural environmental medium, soil has a wide range of sources and is often used as a material for building houses. It can also be used to construct simple protective structures in actual battlefield environments. In order to study the protective effect of sand on prefabricated fragments in practical situations, the authors conducted experiments on spherical tungsten alloy prefabricated fragments penetrating into sand using sand as the target medium. Natural sand (naturally generated rock particles with a particle size less than 4.75 mm) was selected as the sand, and the initial velocities of the fragments were 689 m/s~1761 m/s (fragment diameter 6 mm) and 596 m/s~1325 m/s (fragment diameter 11 mm), respectively. Based on the residual velocity of fragments and experimental phenomena in experimental data, the authors used LS-DYNA software to numerically simulate and compare the residual velocity of fragments and obtained a numerical model for sandy soil media and a calculation formula for the residual velocity of spherical fragments. Based on modeling equivalence in practical environments, the authors studied the impact of different attack angles on fragment trajectory deviation and found that fragments have the highest deviation values at 20° and 70° attack angles. They also analyzed the soil boundary effect within a small scale range, and the effect was significant when the vertical distance was less than 40 mm. The penetration resistance of different thicknesses of soil was calculated, and the maximum soil thickness under prefabricated fragment penetration at different speeds was obtained. The effective protective size of the soil under actual conditions was about 550 mm. This experiment provides a reference for the construction parameters of simple soil defense structures in actual environments.

Radar active deception jamming recognition based on Siamese squeeze wavelet attention network

AbstractActive deception jamming recognition has gained significant attention as a crucial aspect of modern electronic warfare, and a large quantity of jamming recognition methods based on either artificial or deep learning methods have been proposed to date. In actual complex battlefields, the abundant deceptive jamming signals are extremely difficult to obtain and the deceptive jamming signals leveraged by the adversarial jammers are often significantly influenced by noise. To address these challenges a Siamese squeeze wavelet attention network (SSWAN) for radar active deception jamming recognition method is proposed. By constructing a wavelet attention module (WAM), the fine‐grained time‐frequency texture features of echo and jamming signals are preferably extracted even under prohibitively strong noise scenarios. Specifically, the Siamese structure is employed as the main backbone network to measure the similarity between jamming signals and make full use of the training samples; besides, the squeeze learning module is embedded to maintain lightweight and prevent overfitting. Experimental results demonstrate that at a jamming‐to‐noise ratio (JNR) of −8 dB, the proposed method achieves recognition accuracies above 96.3% for 6‐class and multi‐class combinational active deceptive jamming types. Overall, compared to mainstream deep networks, the proposed method exhibits superior advantages in lower JNR ratio and small samples of actual battlefield scenarios.

The influence of penetration angle on anti-penetration performance and reverse penetration ricochet phenomenon of UHMWPE laminates

Penetration angle refers to the angle between the normal of laminates and the projectile trajectory. In actual battlefield conditions, projectiles may hit Ultra-High Molecular Weight Polyethylene fiber (referred to as UHMWPE) laminates from various angles, resulting in ricochet phenomena and secondary injuries. Currently, research on bullets hitting penetrating laminates at a perpendicular angle is relatively well-developed, while research on the penetration of laminates by bullets at other angles is limited. Therefore, this study combined experiments and numerical calculations to investigate the penetration of 7.62 mm steel core projectiles at different angles on UHMWPE laminates. The study found that UHMWPE laminates enhanced bullet resistance through yawing and bending the penetrating projectiles at different angles. The influence of penetration angle on the impact area of the projectile-facing surface, the height of the bulge on the backside, and the penetration depth, as well as the trajectory and morphology of the projectile, were mastered in this study. Notably, a penetration angle of 50° was the limit condition for projectile to produce reverse penetration ricochet phenomenon of projectiles in UHMWPE laminates with a thickness of 30 mm. These research findings provide a theoretical basis and technical support for the bulletproof design of UHMWPE laminates.

Light‐weight deep learning method for active jamming recognition based on improved MobileViT

AbstractIn recent years, there has been significant research focused on identifying jamming signals using neural networks to improve identification accuracy. However, traditional networks require large‐scale datasets for training, which is challenging in small sample scenarios such as actual battlefield jamming signal data. Additionally, the large number of parameters in traditional models presents deployment challenges for devices. To address these issues, this study proposes a lightweight neural network model called MobileViT_CA, an improved version of MobileViT, for jamming recognition in small sample scenarios. MobileViT_CA adopts a coordinate attention mechanism suitable for lightweight networks, which further improves the classification performance of the network. The model converts one‐dimensional jamming signals into two‐dimensional time‐frequency distribution images through time‐frequency analysis and then uses the network for recognition. Compared with traditional neural network models, MobileViT_CA significantly reduces the network parameter volume while maintaining high recognition accuracy, accelerating network inference speed, and reducing hardware requirements. Experimental results show that MobileViT_CA performs well in small sample data. The model's fast learning ability has also been verified by using transfer learning, and the use of Grad‐CAM and t‐SNE to analyse MobileViT_CA demonstrates its advantages in feature recognition and extraction. Overall, this approach has the potential to significantly improve the reliability and effectiveness of jamming recognition systems in battlefield scenarios.

Research on modulation recognition method of multi‐component radar signals based on deep convolution neural network

AbstractModulation recognition of single‐component radar signals has been widely studied in the fewer years. Meanwhile, as the electromagnetic environment in the actual battlefields is ever‐increasingly complicated, the demand for the modulation recognition of multi‐component radar signals is also increasing. However, the modulation recognition of single‐component radar signals performs poorly on multi‐component radar signals. To address this problem, a novel modulation recognition method of multi‐component radar signals based on the deep convolutional neural network with a convolutional block attention module (DCNN‐CBAM) is proposed, and the network architecture mainly includes mobile‐inverted bottleneck convolution (MBConv), Fused‐MBConv, and convolutional block attention module (CBAM). An adaptive optimization algorithm Adam with weighted gradient and dynamic bound is proposed for accelerating convergence speed and generalisation performance. The proposed method can not only recognise dual‐component and three‐component radar signals but also four‐component radar signals. The experimental results demonstrate that the recognition accuracies of all radar signals modulation types are more than 83.57% at −8 dB for dual‐component radar signals, 67.41% for three‐component radar signals, and 57.95% for four‐component radar signals, which verify the better recognition performance of DCNN‐CBAM for multi‐component radar signals. The recognition accuracy of the proposed DCNN‐CBAM for dual‐component radar signals can be up to 95.95% at −6 dB, which shows superior recognition performance over the residual method. This work provides an essential guidance for enhancing the recognition performance of multi‐component radar signals.

Uncertain Sensor–Weapon–Target Allocation Problem Based on Uncertainty Theory

The sensor–weapon–target allocation (S-WTA) is a typical collaborative task allocation problem involved in network-centric warfare (NCW). The existing related studies have a limitation to the nature of cooperation and uncertainty in an air defense battle scenario, and most existing models have the assumption that they are determinate, i.e., the parameters in them are known certainly. For the actual battlefield environment, the asymmetric information in it could lead to the failure of the above assumption, and there are many uncertainties whose frequency can not be evaluated objectively. Based on uncertainty theory, this paper studied the S-WTA problem in an indeterminate battlefield environment. First, we analyze the uncertain factors existing in the actual battlefield environment and their influence on the S-WTA problem, and by considering the threat value of the target, the deviation parameters of the sensor tracking performance and weapon interception performance as uncertain variables, we then establish an uncertain S-WTA (USWTA) model, where the destruction value to targets is regarded as an objective function and four categories of typical constraints are set. Further, an equivalent transformation is presented to convert the unsolvable model into a determinate one by the expected value principle. To solve the proposed model efficiently, a permutation-based representation for the allocation scheme of the USWTA problem is introduced firstly, which can construct a feasible solution efficiently, and on this basis, a constructive heuristic algorithm based on maximum marginal return rule (MMRCH) is designed to construct a feasible solution with high quality. Additionally, a local search (LS) operation is proposed to explore for the better solution locally and further improve the quality of solution obtained by MMRCH. Finally, a set of instances are set to be solved by the designed algorithm, and the simulation experiment demonstrates the superiority of the designed algorithm and the feasibility of the proposed model.

Recognition of Deformation Military Targets in the Complex Scenes via MiniSAR Submeter Images With FASAR-Net

Ground armored weapons have a high detection value in military operations. Satellite synthetic aperture radar (SAR) cannot accurately detect military targets with meter-level sizes limited by resolution of sensors. Airborne SAR have strict experimental conditions and cannot be applied in actual battlefield environments. MiniSAR sensors, which combine the advantages of submeter-level ultrahigh resolutions and flexible flight, play a crucial role in recognizing military targets. In this paper, various small military targets in real complex ground scenarios are detected with the MiniSAR of NUAA. However, there are still two difficulties. First, because of a limitation in the number of flight circles, the number of obtainable military target samples is not sufficient to adapt to the traditional deep learning methods that rely on a large number of image samples. Second, due to the imaging systems and different depression angle of MiniSAR, the SAR images of MiniSAR suffer from the same deformation challenge as the moving and stationary target acquisition and recognition (Mstar) with high depression angle. To address these two challenges, we propose a FASAR-Net framework based on few-shot learning with meta learning and adversarial domain learning, combined with the inherent scattering features of the SAR targets. Furthermore, we validate the reliability and accuracy of this algorithm on Mstar and our datasets, and the result of recognizing small SAR targets is compared with our algorithm and other classical algorithms. We conclude that the proposed algorithm has high accuracy in the recognition of the deformation small targets under the few sample condition.

Design and Implementation of Multi-Cyber Range for Cyber Training and Testing

It is essential to build a practical environment of the training/test site for cyber training and weapon system test evaluation. In a military environment, cyber training sites should be continuously developed according to the characteristics of the military. Weapons with cyber security capabilities should be deployed through cyber security certification. Recently, each military has been building its own cyber range that simulates its battlefield environment. However, since the actual battlefield is an integrated operation environment, the cyber range built does not reflect the integrated battlefield environment that is interconnected. This paper proposes a configuration plan and operation function to construct a multi-cyber range reflecting the characteristics of each military to overcome this situation. In order to test the multi-cyber range, which has scenario authoring and operation functions, and can faithfully reflect reality, the impact of DDoS attacks is tested. It is a key to real-world mission-based test evaluation to ensure interoperability between military systems. As a result of the experiment, it was concluded that if a DDoS attack occurs due to the infiltration of malicious code into the military network, it may have a serious impact on securing message interoperability between systems in the military network. Cyber range construction technology is being developed not only in the military, but also in school education and businesses. The proposed technology can also be applied to the construction of cyber ranges in industries where cyber-physical systems are emphasized. In addition, it is a field that is continuously developing with the development of technology, such as being applied as an experimental site for learning machine learning systems.

Airborne Radar Anti-Jamming Waveform Design Based on Deep Reinforcement Learning.

Airborne radars are susceptible to a large number of clutter, noise and variable jamming signals in the real environment, especially when faced with active main lobe jamming, as the waveform shortcut technology in the traditional regime can no longer meet the actual battlefield radar anti-jamming requirements. Therefore, it is necessary to study anti-main-lobe jamming techniques for airborne radars in complex environments to improve their battlefield survivability. In this paper, we propose an airborne radar waveform design method based on a deep reinforcement learning (DRL) algorithm under clutter and jamming conditions, after previous research on reinforcement-learning (RL)-based airborne radar anti-jamming waveform design methods that have improved the anti-jamming performance of airborne radars. The method uses a Markov decision process (MDP) to describe the complex operating environment of airborne radars, calculates the value of the radar anti-jamming waveform strategy under various jamming states using deep neural networks and designs the optimal anti-jamming waveform strategy for airborne radars based on the duelling double deep Q network (D3QN) algorithm. In addition, the method uses an iterative transformation method (ITM) to generate the time domain signals of the optimal waveform strategy. Simulation results show that the airborne radar waveform designed based on the deep reinforcement learning algorithm proposed in this paper improves the signal-to-jamming plus noise ratio (SJNR) by 2.08 dB and 3.03 dB, and target detection probability by 26.79% and 44.25%, respectively, compared with the waveform designed based on the reinforcement learning algorithm and the conventional linear frequency modulation (LFM) signal at a radar transmit power of 5 W. The airborne radar waveform design method proposed in this paper helps airborne radars to enhance anti-jamming performance in complex environments while further improving target detection performance.

A Study on the Combat Effect and Components of Intangible Combat Force

The purpose of this study is to numerically derive the combat effect of intangible combat power on the battlefield and to confirm the importance of the components of intangible combat power on the derived combat effect. Nearly half of defense spending is used every year to improve defense capabilities for the construction of tangible combat forces, but the expenditure for the construction of intangible forces is insignificant. The reason why it is passive in building intangible combat power is that tangible combat power can be identified as a numerical value, but the increase or decrease in intangible combat power cannot be identified. This imbalance in the construction of tangible and intangible combat forces is likely to halve the integrated exercise of combat power in an actual battlefield. Therefore, for the construction of balanced combat power, research is urgently required to confirm the importance of quantifying and deriving combat effects on how intangible combat power is exerted in combat. In this study, the combat effect of intangible combat power was analyzed in terms of space, time, and combat power, and the difference in the combat results of computer simulation (Vision 21) under the same conditions as those for KCTC combat training was assumed and compared. The analysis results confirmed that the combat effect of the intangible combat force exerted at the KCTC combat site was 28.7%, which did not exert a combat effect of 71.3%. The importance of the components of the intangible combat force that affect the combat effect of the intangible combat force derived in this way was analyzed using a statistical analysis program applying linear regression analysis. The analysis results confirmed the requirements and priorities of future education and training through complementary needs and rankings according to the importance of the components.

A Study on the Combat Effect and Components of Intangible Combat Force

The purpose of this study is to numerically derive the combat effect of intangible combat power on the battlefield and to confirm the importance of the components of intangible combat power on the derived combat effect. Nearly half of defense spending is used every year to improve defense capabilities for the construction of tangible combat forces, but the expenditure for the construction of intangible forces is insignificant. The reason why it is passive in building intangible combat power is that tangible combat power can be identified as a numerical value, but the increase or decrease in intangible combat power cannot be identified. This imbalance in the construction of tangible and intangible combat forces is likely to halve the integrated exercise of combat power in an actual battlefield. Therefore, for the construction of balanced combat power, research is urgently required to confirm the importance of quantifying and deriving combat effects on how intangible combat power is exerted in combat. In this study, the combat effect of intangible combat power was analyzed in terms of space, time, and combat power, and the difference in the combat results of computer simulation (Vision 21) under the same conditions as those for KCTC combat training was assumed and compared. The analysis results confirmed that the combat effect of the intangible combat force exerted at the KCTC combat site was 28.7%, which did not exert a combat effect of 71.3%. The importance of the components of the intangible combat force that affect the combat effect of the intangible combat force derived in this way was analyzed using a statistical analysis program applying linear regression analysis. The analysis results confirmed the requirements and priorities of future education and training through complementary needs and rankings according to the importance of the components.

Study on Delivery of Military Drones and Transport UGVs with Time Constraints Using Hybrid Genetic Algorithms

This paper studies the method of delivering munitions using both drones and UGVs that are developing along with the 4th Industrial Revolution. While drones are more mobile than UGVs, their loading capacity is small, and UGVs have relatively less mobility than drones, but their loading capacity is better. Therefore, by simultaneously operating these two delivery means, each other's shortcomings may be compensated. In addition, on actual battlefields, time constraints are an important factor in delivering munitions. Therefore, assuming an actual battlefield environment with a time limit, we establish delivery routes that minimize delivery time by operating both drones and UGVs with different capacities and speeds. If the delivery is not completed within the time limit, penalties are imposed. We devised the hybrid genetic algorithm to find solutions to the proposed model, and as results of the experiment, we showed the algorithm we presented solved the actual size problems in a short time.

New Training Program for the New Requirements of Combat of Tactical Athletes

Actual theaters of operations are complex contexts where soldiers must face different situations, such as symmetrical, asymmetrical, or close quarter combat. The requirements of the actual battlefield are different to the traditional conditioning military training. This new changing scenario produces an activation of the innate fight or flight defense mechanisms with large activations of the anaerobic metabolic pathways and the sympathetic autonomic nervous system. In these scenarios, the anaerobic, aerobic, and strength demands are so specific and the time to improve all training demands in the units is limited. We propose a new training periodization for the military population based on the latest research into the psychophysiological response of soldiers in actual theaters of operations (actual military missions) and actual civilian models of training and periodization to develop a specific, easy, and reliable periodization model for actual tactical athletes. This training intervention was developed in order to improve operational training according to the demands of actual theaters of operations, based on recent research in military and civilian populations. We tried to conduct a proposal that is easy to apply, with minimal use of material different to what could be found in a military base and that could be implemented in a short period of time.

Optimal Design of Multimissile Formation Based on an Adaptive SA-PSO Algorithm

In an effort to maximize the combat effectiveness of multimissile groups, this paper proposes an adaptive simulated annealing–particle swarm optimization (SA-PSO) algorithm to enhance the design parameters of multimissile formations based on the concept of missile cooperative engagement. Firstly, considering actual battlefield circumstances, we establish an effectiveness evaluation index system for the cooperative engagement of missile formations based on the analytic hierarchy process (AHP). In doing so, we adopt a partial triangular fuzzy number method based on authoritative assessments by experts to ascertain the weight of each index. Then, considering given constraints on missile performance, by selecting the relative distances and angles of the leader and follower missiles as formation parameters, we design a fitness function corresponding to the established index system. Finally, we introduce an adaptive capability into the traditional particle swarm optimization (PSO) algorithm and propose an adaptive SA-PSO algorithm based on the simulated annealing (SA) algorithm to calculate the optimal formation parameters. A simulation example is presented for the scenario of optimizing the formation parameters of three missiles, and comparative experiments conducted with the traditional and adaptive PSO algorithms are reported. The simulation results indicate that the proposed adaptive SA-PSO algorithm converges faster than both the traditional and adaptive PSO algorithms and can quickly and effectively solve the multimissile formation optimization problem while ensuring that the optimized formation satisfies the given performance constraints.

The Role of War Game in Educating and Training the Commanders

The war game is considered to be the most effective means of military training due to the fact that it simulates the reality since it provides a semi-real picture of the weapons and equipment used in the training. Consequently, it provides the trainee with the appropriate environment to freely deal with such weapons as well as military equipment which in turn help the trainee become acquainted with all aspects of use and significantly instill confidence in him when such equipment are actually needed in war. More importantly, war game provides environment similar to what is going on in the actual battlefields allowing the commanders to exercise the training as if they were in a real war. Based on this perspective, the war game has emerged as an advanced training means which provides an analogy of the battle atmosphere to a great extent and gives commanders the opportunity to make decisions. It also helps in providing the commanders with a future view which enables them to plan their future and to deal with any challenges they might encounter. In fact, the role of war play is not only limited to training, but also extends to the aspects of military education, preparation, and development. The notion of war game is not only a means for the commander to have knowledge about the war before it occurs so as to be able to realize whether the decisions taken are right or wrong, but also it has become an effective means on which the armies depend when they train and polish the commanders' capabilities as well as skills. In fact, the concept of war play is not exclusive to the military field but also it is employed by all agencies and departments that require a future vision in training or planning. This paper sheds some light on the notion of war game and its role in training and educating the commanders and staff.

Cooperative Tracking Technology of Single Target Multi-Sensor Based on Cooperative Index

The multi-sensor cooperative tracking problem of single machine moving target is studied in this paper. At present, the uncertainties of covariance and unreasonable setting of expectation threshold in cooperative tracking algorithm are easy to cause frequent switching of radar. Moreover, the existing sensor management is carried out under the same tracking accuracy, which does not meet the needs of the actual battlefield environment. To solve these problems, a multi-sensor cooperation algorithm based on information increment and covariance is proposed. Firstly, the expected threshold of cooperative tracking is revised by using co-variance and information increment. Then, the tracking accuracy of the tracked target is adaptively divided according to the battlefield situation. Finally, the high-precision cooperative tracking of single target multi-sensor is realized by the co-index. Simulation results have verified the effectiveness of the proposed algorithm. Compared with traditional algorithms, proposed algorithm not only solves the frequent problem of radar switch, but also saves more sensor resources and improves the combat and anti-destruction capability of aircraft.

The Archaeology of Forts and Battlefields, by David R. Starbuck and The Archaeology of French and Indian War Frontier Forts, by Lawrence E. Babits and Stephanie Gandulla, eds.

<i>The Archaeology of Forts and Battlefields</i>, by David R. Starbuck and <i>The Archaeology of French and Indian War Frontier Forts</i>, by Lawrence E. Babits and Stephanie Gandulla, eds.

‘A relationship of mutual exploitation’: the evolving ties between the Pentagon, Hollywood, and the commercial gaming sector

ABSTRACTThis article examines the close historical and contemporary ties between the Pentagon and Hollywood from the 1920s until today. Drawing on the US military as an in-depth case study, the article shows the extent to which key military actors view the conduct of war as an arena that stretches well beyond the actual battlefields and includes the production of war movies, film documentaries, computer simulations and first person shooter video games. The article begins with an examination of the ‘Military-Industrial Complex’ and its evolution into what experts have dubbed ‘The Military-Industrial-Media-Entertainment Network (MIME-Net).’ It then focuses on the military’s relationship with the filming industry, with the production of reality TV, and the commercial gaming industry. It thereby investigates, through in-depth interviews with key stakeholders, how this phenomenon has evolved over time and into new areas where games, simulators, and game technologies cross the boundaries between militaries, the defense industry, Hollywood and the commercial gaming sector. And it shows how the advent of digital new technologies have opened new platforms through which militaries seek to boost recruitment, to (re)write military history, and to influence the portrayal of the armed forces in the eyes of the public.

A modified symbiotic organisms search algorithm for unmanned combat aerial vehicle route planning problem

Route planning is the core component of unmanned combat aerial vehicle (UCAV) systems and the premise for implementation of airborne reconnaissance, surveillance, combat, and other tasks. The purpose is to find the optimal flight route under certain constraints, and its essence is a multi-constrained global optimisation problem. This paper presents a modified symbiotic organisms search algorithm based on the simplex method (SMSOS) to solve the UCAV path planning problem. In addition to the flight environment for the fixed threat area, this paper tested the flight environment of the randomly generated threat area because of the complexity of the actual battlefield threat area. After many simulation tests, it was concluded that SMSOS can find the shortest flight path while avoiding the threat areas. The experimental results show that SMSOS has faster convergence speed, higher precision, and stronger robustness than the other main swarm intelligence algorithms for solving the UCAV flight planning problem.