Battlefield Surveillance Research Articles

Multiple adverse weather image restoration: A review

Adverse weather conditions significantly impact the machine vision perception of unmanned platforms such as drones and autonomous vehicles. Therefore, restoring and enhancing images affected by these conditions is crucial. However, there is a lack of a comprehensive systematic review on the latest research progress in unified weather image restoration under all-in-one weather conditions and other factors. In this paper, we survey recent progress in various network architectures for multitask image restoration. Specifically, we review and compare different methods including, U-Net, GAN, Transformer, and U-Net/Transformer hybrids. Additionally, we evaluate publicly available datasets for single-task scenarios and compare the performance of these methods comprehensively, and analyze corresponding evaluation metrics. Based on these findings, we believe that Transformer and U-Net models are particularly promising for multi-task image restoration. Nevertheless, further research is needed to fully explore this area. Researchers can improve the image restoration effect from aspects such as data dynamic flow, encoder–decoder internal structure, etc. These insights contribute to advancing image acquisition technologies and addressing challenges in military image information retrieval, including military reconnaissance, terrain analysis, target identification, and battlefield surveillance.

Survey of UAV Security Authentication and Cryptography Protocols

Unmanned aerial vehicles, or UAVs, are gaining significant attention because of the strategic and financial information and value involved in aerial applications, as well as the sensitive data collected through embedded sensors. UAVs are rapidly developing in various fields and find widespread utility in military applications for effective target tracking, battlefield surveillance, radiation monitoring, and sports. UAVs are useful and advantageous, but they can also be attacked by a variety of techniques, including jamming, fuzzing, false data injection, and zero attacks. Researchers were looking on robust security mechanisms to protect UAVs from attackers in order to combat such security risks. However, there is a large number of vulnerabilities in designed protocols that hackers could take advantage of. For the identification and addressing of those vulnerabilities and weaknesses, it is becoming highly important to study and analyze current security protocols that are used in the UAVs. In this study, a thorough survey will be introduced on authentication and cryptography that are used in the UAV protocols, as well as describing architecture, procedure, and security of Micro Aerial Vehicle Link (MavLink) protocol. We will explain as well the cryptography and authentication approach that has been developed by the use of the MavLink protocol. Index Terms— UAV, Unmanned Aerial Vehicles, MavLink, Zero attack.

A Novel Mamba Architecture with a Semantic Transformer for Efficient Real-Time Remote Sensing Semantic Segmentation

Real-time remote sensing segmentation technology is crucial for unmanned aerial vehicles (UAVs) in battlefield surveillance, land characterization observation, earthquake disaster assessment, etc., and can significantly enhance the application value of UAVs in military and civilian fields. To realize this potential, it is essential to develop real-time semantic segmentation methods that can be applied to resource-limited platforms, such as edge devices. The majority of mainstream real-time semantic segmentation methods rely on convolutional neural networks (CNNs) and transformers. However, CNNs cannot effectively capture long-range dependencies, while transformers have high computational complexity. This paper proposes a novel remote sensing Mamba architecture for real-time segmentation tasks in remote sensing, named RTMamba. Specifically, the backbone utilizes a Visual State-Space (VSS) block to extract deep features and maintains linear computational complexity, thereby capturing long-range contextual information. Additionally, a novel Inverted Triangle Pyramid Pooling (ITP) module is incorporated into the decoder. The ITP module can effectively filter redundant feature information and enhance the perception of objects and their boundaries in remote sensing images. Extensive experiments were conducted on three challenging aerial remote sensing segmentation benchmarks, including Vaihingen, Potsdam, and LoveDA. The results show that RTMamba achieves competitive performance advantages in terms of segmentation accuracy and inference speed compared to state-of-the-art CNN and transformer methods. To further validate the deployment potential of the model on embedded devices with limited resources, such as UAVs, we conducted tests on the Jetson AGX Orin edge device. The experimental results demonstrate that RTMamba achieves impressive real-time segmentation performance.

Invasive weed optimization based compact hybridized fractal antenna design for RF energy harvesting and multifunctional wireless applications

This paper describes the optimal design and analysis of compact multiband Hybrid Fractal Antenna using Invasive Weed Optimization (HFAIWO). The configured structure involves the fusion of Minkowski, Sierpinski carpet and Giuseppe Peano in a coherent manner. The two-iterative conglomerated fractal antenna is realized physically by considering FR4 epoxy material (dielectric constant, εr = 4.4 and mass density = 1,900 kg/m3). The volumetric dimensions of the fabricated prototype are 36 x 36 x 1.6 mm3. In the designing process, the geometrical descriptors, namely, feedline width ‘WF’ and ground plane dimension ‘LG’ are optimized specifically using Invasive Weed Optimization (IWO) and Harmony Search Algorithm (HSA) strategies. The optimal solution is searched by changing the descriptor values under a set of practical constraints. The examined values of ‘WF’ and ‘LG’ using IWO and HSA are 3 and 31 mm, and 2.6 and 28.7 mm, respectively. Comparative results reveal that IWO offers superior solution quality and convergence than HSA. Afterwards, experimentation of the Projected HFAIWO is done to justify the recommended fractal hybridization approach. Measurements reveal that for VSWR ≤ 2, the fabricated structure produces nine resonance points (1.84, 3.99, 5.15, 5.55, 6.30, 6.58, 8.00, 9.29, and 12.01 GHz) with appreciable gain values. At the respective resonance points, the −10 dB impedance bandwidth is 3.9 %, 3.1 %, 2.1 %, 2.2 %, 1.4 %, 1.2 %, 6.9 %, 1.2 %, and 12.23 %. The provided radiation patterns are arbitrary bidirectional/omnidirectional. By applying the above-said approaches, the radiator size is reduced by 54 %. Importantly, the constructed structure covers two important bands i.e. 1.84 GHz (GSM 1800 band, downlink) and 5.55 GHz (WLAN (Lower) 5.150–5.725 GHz) associated with energy harvesting applications. The practical outcomes suggest that the introduced prototype is a proficient candidate for energy harvesting systems, Satellite communication for downlink, Long range tracking, Battlefield surveillance, Digital broadcast satellite service, Weather Radar, and Maritime navigation radar.

Reconfigurable Intelligent Surface Assisted Target Three-Dimensional Localization with 2-D Radar

Battlefield surveillance radar is usually 2-D radar, which cannot realize target three-dimensional localization, leading to poor resolution for the air target in the elevation dimension. Previous researchers have used the Traditional Height Finder Radar (HFR) or multiple 2-D radar networking to estimate the target three-dimensional location. However, all of them face the problems of high cost, poor real-time performance and high requirement of space–time registration. In this paper, Reconfigurable Intelligent Surfaces (RISs) with low cost are introduced into the 2-D radar to realize the target three-dimensional localization. Taking advantage of the wide beam of 2-D radar in the elevation dimension, several Unmanned Aerial Vehicles (UAVs) carrying RISs are set in the receiving beam to form multiple auxiliary measurement channels. In addition, the traditional 2-D radar measurements combined with the auxiliary channel measurements are used to realize the target three-dimensional localization by solving a nonlinear least square problem with a convex optimization method. For the proposed RIS-assisted target three-dimensional localization problem, the Cramer–Rao Lower Bound (CRLB) is derived to measure the target localization accuracy. Simulation results verify the effectiveness of the proposed 3-D localization method, and the influences of the number, the positions and the site errors of the RISs on the localization accuracy are covered.

Meta Heuristic Technique with Reinforcement Learning for Node Deployment in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are vital in applications like environmental monitoring, smart homes, and battlefield surveillance. Comprising small devices with limited resources, WSNs require efficient node deployment for power optimization and prolonged network lifetime, ensuring sufficient coverage and connectivity. This study introduces an Intelligent Satin Bower Bird Optimizer augmented with reinforcement learning (ISBO-RL), enhancing coverage and connectivity. ISBO-RL focuses on optimal sensor placement for improved coverage and connectivity, using an Optimum Position Finding (OPF) method to identify key sensor node locations. Reinforcement learning is integrated into the ISBO algorithm, allowing nodes to adapt based on performance and changing conditions. Experimental results on diverse platforms highlight ISBO-RL’s efficacy and its superior coverage and connectivity performance as compared to other algorithms. ISBO-RL represents a significant advancement in the field of Wireless Sensor Networks, offering a promising solution to address the challenges of efficient node deployment and network optimization in various critical applications.

Evaluating Trust Management Frameworks for Wireless Sensor Networks.

Wireless Sensor Networks (WSNs) are crucial in various fields including Health Care Monitoring, Battlefield Surveillance, and Smart Agriculture. However, WSNs are susceptible to malicious attacks due to the massive quantity of sensors within them. Hence, there is a demand for a trust evaluation framework within WSNs to function as a secure system, to identify and isolate malicious or faulty sensor nodes. This information can be leveraged by neighboring nodes, to prevent collaboration in tasks like data aggregation and forwarding. While numerous trust frameworks have been suggested in the literature to assess trust scores and examine the reliability of sensors through direct and indirect communications, implementing these trust evaluation criteria is challenging due to the intricate nature of the trust evaluation process and the limited availability of datasets. This research conducts a novel comparative analysis of three trust management models: "Lightweight Trust Management based on Bayesian and Entropy (LTMBE)", "Beta-based Trust and Reputation Evaluation System (BTRES)", and "Lightweight and Dependable Trust System (LDTS)". To assess the practicality of these trust management models, we compare and examine their performance in multiple scenarios. Additionally, we assess and compare how well the trust management approaches perform in response to two significant cyber-attacks. Based on the experimental comparative analysis, it can be inferred that the LTMBE model is optimal for WSN applications emphasizing high energy efficiency, while the BTRES model is most suitable for WSN applications prioritizing critical security measures. The conducted empirical comparative analysis can act as a benchmark for upcoming research on trust evaluation frameworks for WSNs.

Departure Device Design With Dual Redundancy for the Assistant Landing Gear of Long-endurance UAV

In modern wars and regional conflicts, in order to reduce casualties, more and more unmanned equipment and weapons are utilized. Among them, the UAV is the new favorite in the sky. Application fields of the military UAV are wide and varied. It is found to be used for intelligence reconnaissance, battlefield surveillance, as well as strikes. As for the scout UAV, long endurance is of utmost importance. There is no denying that less weight can result in longer endurance. A departure device for the assistant landing gear of a long-endurance UAV is designed in this paper. The system constitution and working principles are introduced in the beginning. Then, detailed system designs are presented, including the hardware design, software design, and other parts of the departure device. Several static and dynamic experiments are conducted to prove its feasibility. At last, the conclusion part summarizes its applications.

Advances in Aerial Image Exploitation

The availability of low cost sensors, high bandwidth communication links and the growing popularity of Unmanned Aerial Reconnaissance Platforms like UAVs have resulted in dramatic new opportunities to conduct remote battlefield surveillance and reconnaissance missions from relatively safe Ground Control Stations. The sensors used in UAV explore the visible, infrared and microwave regions of the spectrum and the images are produced optically, electronically or by film. Aerial Image Exploitation is an innovative image utilization program that uses multi sensor, multi resolution and multi spectral imagery obtained from Aerial Reconnaissance Platform for the purpose of Extraction, Exploitation, Dissemination and Interpretation of Imagery Intelligence. Research in aerial image exploitation is focused to provide a total solution of the problem by combining both hardware and software at the system and subsystem level. Major operational goal of image exploitation technology is to extract the vital intelligence from a large storehouse of available imagery by filtering those which are most likely to produce valuable findings, to combine classical image/signal processing techniques with technologies available in other fields and to use specialized hardware wherever required. The first part of the paper describes the Ground Image Exploitation System and Imagery Intelligence Exploitation System being developed in ADE. The second part of the paper describes some of the basic and advanced research work being carried out in ADE, which is the backbone that lead to the development of these systems. Some of the areas discussed in this paper are adaptive preprocessing of imagery, image mosaicing, terrain classification and high-resolution reconstruction of target region.

Clustering based secure error report fault tolerant routing in mobile adhoc networks

A Mobile Ad-hoc Network (MANET) is a self-constructed network consisting of spatially distributed nodes that cooperatively arrange themselves without any centralized manager or fixed based stations. In MANET, the nodes are deployed in a dynamic scenario, so, the nodes may fail as a result of energy depletion, hardware failure, communication link errors, and malicious attacks. Therefore, it is necessary to design energy-efficient fault-tolerant algorithms and protocols for MANETs. Since the development of Mobile Ad-hoc networks was originally motivated by military applications, such as battlefield surveillance and healthcare applications it is required to have a fast recovery mechanism to overcome the fault condition. In this research work, a fault-tolerant Routing mechanism is designed and implemented to address the fault conditions such as node failure, link failure, and critical battery issues called Fault tolerant cluster based AODV with Error Reporting Routing (CAODVERR) protocol, and to improve the stability of the MANET. Also, an Error reporting mechanism has been incorporated with the Ad-hoc On-Demand Distance Vector (AODV) routing protocol.

Distributed Control of Cyber Physical System on Various Domains: A Critical Review

Cyber-Physical System (CPS) is a symbol of the fourth industrial revolution (4IR) by integrating physical and computational processes which can associate with humans in various ways. In short, the relationship between Cyber networks and the physical component is known as CPS, which is assisting to incorporate the world and influencing our ordinary life significantly. In terms of practical utilization of CPS interacting abundant difficulties. Currently, CPS is involved in modern society very vastly with many uptrend perspectives. All the new technologies by using CPS are accelerating our journey of innovation. In this paper, we have explained the research areas of 14 important domains of Cyber-Physical Systems (CPS) including aircraft transportation systems, battlefield surveillance, chemical production, energy, agriculture (food supply), healthcare, education, industrial automation, manufacturing, mobile devices, robotics, transportation, and vehicular. We also demonstrated the challenges and future direction of each paper of all domains. Almost all articles have limitations on security, data privacy, and safety. Several projects and new dimensions are mentioned where CPS is the key integration. Consequently, the researchers and academicians will be benefited to update the CPS workspace and it will help them with more research on a specific topic of CPS. 158 papers are studied in this survey as well as among these, 98 papers are directly studied with the 14 domains with challenges and future instruction which is the first survey paper as per the knowledge of authors.

Early Forest Fire Detection Using a Protocol for Energy-Efficient Clustering with Weighted-Based Optimization in Wireless Sensor Networks

Wireless sensor networks (WSNs) have proven to be incredibly useful for forest applications that rely on sensing technologies for event detection and monitoring. This radical sensing technology has revolutionized data gathering, analysis, and application. Despite the many advantages of this technology, one key drawback is the rapid drain on sensor batteries caused by their intensive processing activities and communication processes. The effectiveness of sensor nodes is strongly influenced by two factors: the amount of energy they consume and the length of their coverage lifetimes. Using our proposed method, we can find fire zones in a forest, detect and monitor battlefield surveillance, combat monitoring and intruder detection, and then wirelessly send all the information to a central station. So, extending the life of WSNs is essential to ensure that Sensor Nodes (SN) will always be available. Our proposed EEWBP (energy-efficient weighted-based protocol) technique uses a composite weighted metric that includes system elements such as the node degree, residual energy, the number of neighbors’ nodes, average flying speed, and trust value, which are evaluated separately and then added together to help in cluster-building and node-scheduling processes. Our proposed protocol makes it easy to set up many clusters of SNs, each with their own cluster head (CH). This way, data can be sent between clusters in a way that uses the least amount of energy and makes coverage last longer. After putting our cluster-based routing strategy in place, we tested how it worked and evaluated it with different network parameters. The simulation results show that EEWBP consumes less energy and maintains a higher level of consistency in the CH than coverage preserving clustering protocol (CPCP), coverage clustering protocol (CACP), coverage aware unequal clustering algorithm (CUCA), and low-energy adaptive clustering hierarchy (LEACH). EEWBP also shows a better packet delivery rate and an improvement in first-node death.

Is drone becoming the new “apparatus of domination”?: Battlefield surveillance in the twenty-first century warfare

The paper looks at the military use of burgeoning technologies of the Fourth Industrial Revolution in designing the visual regime of the drone as a tool for control of combat efficiency in twenty-first-century warfare. The author posits his analysis in critical theory and critical war/military studies with focus on the operationally relevant use of technical properties of the visual regime of drone observed through a wealth of video material uploaded to YouTube and related to the ongoing war in Ukraine. While many analyses delve into the combined practices of intelligence gathering, targeting, and killing aimed at the enemy, the author investigates how recent combat practices unveil the potential for an emerging role of drone surveillance: the scrutinization of combat performance of one?s own soldiers. In the age of a highly professionalized and industrialized warfare, inherent to the politics of military interventionism aimed at maintaining liberal peace across the globe, the shift towards a pervasive control over the combat ?assembly line? reconstitutes technological character of the drone so that it becomes an apparatus of domination. The author concludes that the drone as mobile platform for surveillance displays hidden potentials to reinforce the existing relations of domination and cautions that the advent of nano-drones could socially constitute far more intrusive and intimate control of ground troops.

IACRA: Lifetime Optimization by Invulnerability-Aware Clustering Routing Algorithm Using Game-Theoretic Approach for Wsns.

Energy limitation is one of the intrinsic shortcomings of wireless sensor networks (WSNs), although it has been widely applied in disaster response, battlefield surveillance, wildfire monitoring, radioactivity detection, etc. Due to the large amount of energy consumed for data transmission, how to prolong the network lifespan by designing various hierarchical routing protocols has attracted more and more attention. As a result, numerous achievements have emerged successively. However, these presented mechanisms can rarely guarantee the satisfactory quality of service (QoS), while lowering the energy cost level of WSNs. Meanwhile, invulnerability is undoubtedly an excellent quantitative index to assess QoS. Therefore, it is critical to develop a practical routing method to optimize network lifetime by considering both invulnerability and energy efficiency. Game theory is suitable for such a critical problem as it can be used in node or at network level to encourage the decision-making capabilities of WSNs. In this paper, a novel invulnerability-aware clustering routing algorithm (IACRA) using game-theoretic method is proposed to solve the predicament. The core features of the addressed game-theory-based routing protocol include integral invulnerability awareness, optimal cluster head selection in hierarchical routing, distance-aware cluster head discovery, and cluster rotation update mechanism for lifetime optimization. Particularly, the integral network invulnerability based on weighted fusion is constructed for further defining the profit model by combining the invulnerability indicators used to evaluate the local and whole network. Meanwhile, the optimal probability function of every node elected as CH in per cluster is established through the game between invulnerability and node energy consumption. In addition, the cluster update mechanism base on cluster rotation is proposed to avoid the rapid death of nodes with large energy consumption for maximizing network lifetime. The experimental results indicated a significant improvement in energy balance as well as in invulnerability compared with the other three kinds of well-known clustering routing protocols including GEEC (Game-theory-based energy efficient clustering routing protocol), HGTD (Hybrid, game-theory-based distributed clustering protocol), and EEGC (Efficient energy-aware and game-theory-based clustering protocol). Concretely, at the 400 communication rounds, the invulnerability of IACRA was higher than that of GEEC, HGTD, and EEGC by 77.56%, 29.45% and 15.90%, respectively, and the average residual energy of IACRA was 8.61%, 18.35% and 6.36% larger than that of GEEC, HGTD, and EEGC, respectively. Based on these results, the proposed protocol can be utilized to increase the capability of WSNs against deterioration of QoS and energy constraints.

An approach to data redundancy reduction and secured data delivery using spatial‐temporal correlation factors in heterogeneous Mobile Wireless Sensor Network

SummaryAs the state‐of‐the‐art technology in the areas of IoT, battlefield surveillance, medical, military applications, and so on, the Mobile Wireless Sensor Network (MWSN) has attracted the attention of vendors and academics in recent years. In MWSN, energy optimization is the major issue because of its dynamicity property. The energy optimization can be achieved by avoiding node compromise attacks and ensuring secured data transmission in the network. In this paper, an algorithm SDCH‐M (Secured Data for Mobile Clustering Hierarchy) is proposed to ensure secure data delivery in a double cluster head hybrid topology, which optimizes the network energy consumption. Data redundancy is reduced by estimating spatial‐temporal correlation factors, and the variant‐round voting mechanism is used to verify the accuracy of delivered data and to identify compromised nodes through voting by the base station. Results from the simulation show that the proposed SDCH‐M algorithm optimizes energy than M‐LEACH and C‐LEACH algorithm. The average delivery ratio of SDCH‐M (DCH), SDCH‐M (SCH), E2RP, M‐LEACH, and C‐LEACH are 0.9175, 0.9037, 0.828, 0.799, and 0.681, respectively. The average delay of M‐LEACH, C‐LEACH, E2RP, SDCH‐M (DCH), and SDCH‐M (SCH) algorithms is 6.851, 8.655, 6.3, 5.585, and 5.97 s, respectively.

Secure Protocol for Resource-Constrained IoT Device Authentication

Wireless sensor networks (WSNs) are crucial components of internet of things (IoT) and have been deployed in numerous fields such as battlefield surveillance. The exploitation of broadcasts in WSNs renders these networks susceptible to numerous attacks. Consequently, to boost security, reliability, and successful cooperation, trust must be established among the sensor nodes. Unfortunately, the current authentication and authorization approaches exhibit high key management overheads, depend on static digital signatures or trusted third parties, and have both high communication latencies and computational complexity that render them inefficient. In this paper, challenge-response mutual authentication protocol is proposed for enhancing security in WSN-based IoT environment. The simulation results showed that the proposed protocol has the least transaction costs, time complexity, end to end delays and energy consumptions. It is also resilient against dictionary, side channel, cloning, man-in-the-middle (MitM, denial of service (DoS) and next password prediction attacks.

BLOCKCHAIN BASED SECURE ANDENERGY EFFICIENT ROUTING PROTOCOLFORWSN

Routing in a Wireless Network Sensor (WSN) is a critical process as it is basically responsible for transmitting the data to Base Stations (BS). WSNs are used in a wide range of applications that require the data to be transmitted and received securely, such as in battlefield surveillance, flood detection, forest fire detection, traffic surveillance, etc. But the actual routing process is susceptible to attacks that can completely destroy the operation of the WSN. The intervention from malicious nodes is one of them. Malicious nodes can send erroneous information of particular lengths to other nodes in order to increase their chance of receiving the data that is being transmitted. The malicious nodes can also send corrupted data to other nodes and cause the operation of WSNs to fail. Hence, a trustworthy routing system is a must in orderto ensure that the WSN will operate smoothly and efficiently. An authentication scheme is introduced that is blockchain-based, so as to provide secure routing in the WSNs. As there are unauthenticated and malicious nodes that affect the routing process, the correct identification of the routing path becomes a challenging issue. Therefore, in our model, to prevent the involvement of these malicious nodes in the network, the registration of the nodes is done by a Certificate Authority Node. Each node that is involved in the routing gets authenticated by the BS and a mutual authentication is also performed. Furthermore, in the proposed routing protocol, a Cluster Head (CH)is used. The selection of a CH node is based on the residual energy of the node and the node which has the minimum distance from BS. This CH collects the data from the other nodes and sends it forwards to the BS. Every node can authenticate the process of transmitting or receiving data using a Proof of Authority (PoA) method in the blockchain network.

Lightweight Challenge-Response Authentication in SDN-Based UAVs Using Elliptic Curve Cryptography

Unmanned aerial vehicles (UAVs) (also known as drones) are aircraft that do not require the presence of a human pilot to fly. UAVs can be controlled remotely by a human operator or autonomously by onboard computer systems. UAVs have many military uses, including battlefield surveillance, effective target tracking and engagement in air-to-ground warfare, and situational awareness in challenging circumstances. They also offer a distinct advantage in various applications such as forest fire monitoring and surveillance. Surveillance systems are developed using advanced technologies in the modern era of communications and networks. As a result, UAVs require enhancements to control and manage systems efficiently. Network security is a critical concern with respect to UAVs due to the risk of surveillance information theft and physical misuse. Although several new tools have been introduced to secure networks, attackers can use more advanced methods to get into a UAV network and create problems that pose an organizational threat to the entire system. Security mechanisms also reduce the performance of systems because some restrictive measures prevent users from accessing specific resources, but a few techniques and tools have overcome the problem of performance reduction in various scenarios. There are many types of attacks, i.e., denial of service attacks (DOS), distributed denial of service attacks (DDOS), address resolution protocol (ARP) spoofing, sniffing, etc., that make it challenging to maintain a UAV network. This research paper proposes a lightweight challenge-response authentication that can overcome the previously mentioned problems. As security is provided by utilizing a minimum number of bits in memory, this technique offers the same security features while using fewer network resources, low computing resources, and low power consumption.

Using Adaptive Sensors for Optimised Target Coverage in Wireless Sensor Networks.

Innovation in wireless communications and microtechnology has progressed day by day, and this has resulted in the creation of wireless sensor networks. This technology is utilised in a variety of settings, including battlefield surveillance, home security, and healthcare monitoring, among others. However, since tiny batteries with very little power are used, this technology has power and target monitoring issues. With the development of various architectures and algorithms, considerable research has been done to address these problems. The adaptive learning automata algorithm (ALAA) is a scheduling machine learning method that is utilised in this study. It offers a time-saving scheduling method. As a result, each sensor node in the network has been outfitted with learning automata, allowing them to choose their appropriate state at any given moment. The sensor is in one of two states: active or sleep. Several experiments were conducted to get the findings of the suggested method. Different parameters are utilised in this experiment to verify the consistency of the method for scheduling the sensor node so that it can cover all of the targets while using less power. The experimental findings indicate that the proposed method is an effective approach to schedule sensor nodes to monitor all targets while using less electricity. Finally, we have benchmarked our technique against the LADSC scheduling algorithm. All of the experimental data collected thus far demonstrate that the suggested method has justified the problem description and achieved the project’s aim. Thus, while constructing an actual sensor network, our suggested algorithm may be utilised as a useful technique for scheduling sensor nodes.

РОЗВИТОК БЕЗПІЛОТНОЇ АВІАЦІЇ У СВІТІ ТА УКРАЇНІ: АНАЛІЗ ОСОБЛИВОСТЕЙ ТА ТЕХНІЧНИХ ХАРАКТЕРИСТИК

The capabilities of unmanned aerial vehicles are constantly growing, the scope of their use is expanding, combat survivability is increasing. Most of them are small, low optical and radar contrast, so they are less vulnerable to enemy air defenses. At the same time, in the armed forces of the world's leading countries, in particular the Armed Forces of Ukraine, unmanned aerial vehicles are increasingly used instead of manned aircraft to perform combat tasks of reconnaissance, battlefield surveillance, destruction of ground targets, creation of false air targets and more. In general, the assessment of modern armed conflicts shows an increase in the intensity of mass use of unmanned aerial vehicles to solve combat tasks at various levels (tactical, operational and strategic), which significantly changes the course of armed struggle in the air. Unmanned aerial vehicles have been and remain one of the main means, which determines not only the enthusiasm of the initiative, but also the result of the confrontation in general. Analysis of publications allows us to understand the use of unmanned aerial vehicles, the effectiveness of unmanned aerial vehicles in solving various problems, as well as their advantages and disadvantages, but does not reveal ways and experience of using unmanned aerial vehicles in today's military conflict. This article reveals the trends in the combat use of unmanned aerial vehicles, analyzes the use of unmanned aerial vehicles based on the experience of their combat use in combat conflict with the Russian Federation, which, in particular, showed that the struggle of air defense forces and forces in the armed conflict Aviation is ineffective due to a number of factors, in particular due to the advanced development of these air attack means in relation to existing air defense firepower. In addition, the paper identifies the importance of unmanned aerial vehicles on the peculiarities of warfare, its further nature of action and trends in the further application and features of modern martial arts with the leading role of aviation. Thus, the air operation (both for defense and offensive purposes) is an important component of the operation to repel armed aggression and aggravate the military-political conflict and full-scale armed conflict of the Russian Federation requires a more detailed analysis of combat applications of modern unmanned aerial vehicles.