Search Results (459)

Cross-modal remote sensing object detection holds significant potential for around-the-clock applications. However, the modality differences between cross-modal data and the degradation of feature quality under adverse weather conditions limit detection performance. To address these challenges, this paper presents a novel cross-modal remote sensing object detection framework designed to overcome two critical challenges in around-the-clock applications: (1) significant modality disparities between visible light, infrared, and synthetic aperture radar data, and (2) severe feature degradation under adverse weather conditions including fog, and nighttime scenarios. Our primary contributions are as follows: First, we develop a multi-scale feature extraction module that employs a hierarchical convolutional architecture to capture both fine-grained details and contextual information, effectively compensating for missing or blurred features in degraded visible-light images. Second, we introduce an innovative feature interaction module that utilizes cross-attention mechanisms to establish long-range dependencies across modalities while dynamically suppressing noise interference through adaptive feature selection. Third, we propose a feature correction fusion module that performs spatial alignment of object boundaries and channel-wise optimization of global feature consistency, enabling robust fusion of complementary information from different modalities. The proposed framework is validated on visible light, infrared, and SAR modalities. Extensive experiments on three challenging datasets (LLVIP, OGSOD, and Drone Vehicle) demonstrate our framework’s superior performance, achieving state-of-the-art mean average precision scores of 66.3%, 58.6%, and 71.7%, respectively, representing significant improvements over existing methods in scenarios with modality differences or extreme weather conditions. The proposed solution not only advances the technical frontier of cross-modal object detection but also provides practical value for mission-critical applications such as 24/7 surveillance systems, military reconnaissance, and emergency response operations where reliable around-the-clock detection is essential. Full article

Inconsistency in the structural strengths of a membrane wing under positive and negative loads has undesirable impacts on the aeroelastic deflections of the wing, which results in more significant flight control system modeling errors and worsens the performance of the aircraft. In this paper, an integrated dynamic model is derived for a membrane-wing aircraft based on the structural dynamics equation of the membrane wing and the flight dynamics equation of the traditional fixed wing. Based on state feedback control theory, an autopilot system is designed to unify the flight and control properties of different flight and wing deformation statuses. The system uses models of different operating regions to estimate the dynamic response of the vehicle and compares the estimation results with the sensor signals. Based on the compared results, the autopilot can identify the overall flight and select the correct operating region for the control system. By switching to the operating region with the minimum modeling error, the autopilot system maintains good flight performance while flying in turbulence. According to the simulation results, compared with traditional rigid aircraft autopilots, the proposed autopilot can reduce the absolute maximum attack angles by nearly 27% and the absolute maximum wingtip twist angles by nearly 25% under gust conditions. This enhanced robustness and stability performance demonstrates the autopilot’s significant potential for practical deployment in micro-aerial vehicles, particularly in applications demanding reliable operation under turbulent conditions, such as military surveillance, environmental monitoring, precision agriculture, or infrastructure inspection. Full article

In this article, we present a case study of the waste collection problem at the Hellenic Military Academy. The waste is sorted by type and collected by a garbage truck. To minimize the travel cost of the waste collection vehicle, we apply the Markov Decision Process methodology. This approach enables the development of more efficient algorithms. Full article

In recent years, the use of unmanned aerial vehicles (UAVs), commonly known as drones, has significantly surged across civil, military, and commercial sectors. Ensuring reliable and efficient communication between UAVs and between UAVs and base stations is challenging due to dynamic factors such as altitude, mobility, environmental obstacles, and atmospheric conditions, which existing communication models fail to address fully. This paper presents a multi-ray channel model that captures the complexities of the airspace network, applicable to both ground-to-air (G2A) and air-to-air (A2A) communications to ensure reliability and efficiency within the network. The model outperforms conventional line-of-sight assumptions by integrating multiple rays to reflect the multipath transmission of UAVs. The multi-ray channel model considers UAV flights’ dynamic and 3-D nature and the conditions in which UAVs typically operate, including urban, suburban, and rural environments. A technique that calculates the received power at a target UAV within a networked airspace is also proposed, utilizing the reflective characteristics of UAV surfaces along with the multi-ray channel model. The developed multi-ray channel model further facilitates the characterization and performance evaluation of G2A and A2A communications. Additionally, this paper explores the effects of various factors, such as altitude, the number of UAVs, and the spatial separation between them on the power received by the target UAV. The simulation outcomes are validated by empirical data and existing theoretical models, providing comprehensive insight into the proposed channel modelling technique. Full article

Nowadays, many various types of drive and transmission mechanisms characterized by various parameters and characteristics for different types of vehicles have been designed, developed and optimized with regard to the featured applications. Our research is focused on the creation of a complex simulation model of the drive and transmission mechanism of the vehicle Iveco LMV 4 × 4 M65. The correctness of the simulation model was verified using an analytical approach. The created numerical simulation model will serve as a basis for the further optimization of dynamic, operational and economical parameters of the vehicle. As the modification or replacement of the particular components of the drive and transmission mechanism is very complicated regarding the vehicles used in military operations, our research is focused on the enhancement of the control processes. More specifically, the main goal of the presented research activities is the modification of the gearshift logic and the adjustment of the gearshift map in order to improve the dynamic properties of the vehicle and, at the same time, reduce the fuel consumption. In spite of its complexity, the proposed simulation model can serve as a basis for the optimization of not only the gearshift control under specific input or output quantities and operational or environmental conditions but also for the simulation of the system behavior with modified or replaced components of the drive and transmission mechanism of this type of truck vehicle. Full article

This study explores the mechanical performance of triply periodic minimal surface (TPMS) and stochastic lattice structures subjected to low-velocity impact. Two structurally promising geometries—one TPMS-based and one stochastic—were tested and compared with the well-established gyroid. Specimens were fabricated using stereolithography (SLA) and subjected to impact energies of 30 J and 40 J to assess the structural response and energy absorption capabilities. Experimental results show that the proposed TPMS structure exhibits higher impact forces compared with the gyroid, which are associated with significant impactor displacement and deep indentation. These samples demonstrated extensive damage, with cracking propagating through the entire core at higher energies, highlighting their susceptibility to structural failure despite their high initial strength. On the contrary, the stochastic structures allowed localized deformation in the impacted region, thus successfully avoiding catastrophic failure. The impact force efficiency was higher for both gyroid and stochastic geometries, with values ranging between 0.6 and 0.7, indicating effective energy absorption with reduced internal stress gradients. Furthermore, the evaluation of damping performance showed that most structures displayed high damping, as minimal energy was transferred back to the impactor. This work highlights the feasibility and functional versatility of TPMS and stochastic geometries for use in impact mitigation, vibration control, and related engineering applications. Full article

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

A previously buried paleosol was found on the continental shelf during a study of sea floor scour, nucleated by large artificial reef structures such as vessel hulks, barges, train cars, military vehicles, etc., called “scour nuclei”. It is a relic paleo-land surface of sapling-sized tree stumps, root systems, and fossil animal bone exhumed by scour processes active adjacent to the artificial reef structure. Over the span of five research cruises to the site in 2022–2024, soil samples were taken using hand excavation, PONAR grab samplers, split spoon, hollow tube auger, and a modified Shelby-style push box. High-definition (HD) video was taken using a Remotely Operated Vehicle (ROV) and diver-held cameras. Radiocarbon dating of wood samples returned ages of 42,015–43,417 calibrated years before present (cal yrBP). Pollen studies, together with the recovered macrobotanical remains, support our interpretation of the site as a freshwater forested wetland whose keystone tree species was Taxodium distichum—bald cypress. The paleosol was identified as an Aquult, a sub-order of Ultisols where water tables are at or near the surface year-round. A deep (0.25 m+) argillic horizon comprised the bulk of the preserved soil. Comparable Ultisols found in Georgia wetlands include Typic Paleaquult (Grady and Bayboro series) soils. Full article

The civil and military use of autonomously or remotely controlled unmanned aerial vehicles (UAVs) has become standard in many sectors. However, their role as supplementary vehicles for helicopter emergency medical services (HEMS) or search and rescue (SAR)—particularly when aiding individuals in hard-to-reach terrains—remains underexplored and in need of further innovation. The feasibility of using UAVs in such operations depends on multiple factors, including legislative, economic, and market conditions. However, the most critical considerations are external factors that impact UAV flight, such as meteorological conditions (wind speed and direction), the designated operational area, the proficiency of the pilot–operator, and the classification and certification of the UAV, particularly if it has been modified for such missions. Additionally, the feasibility of the remote or autonomous control of the UAV in mountainous environments plays a crucial role in determining their effectiveness. Establishing a specialized simulation environment to address these challenges is essential for assessing UAV performance in mountainous regions. This is particularly relevant in the Slovak Republic, a very rugged landscape, where the planned expansion of UAV-assisted rescue operations must be preceded by thorough testing, flight verification, and operational planning within protected landscape areas. Moreover, significant legislative changes will be required, which can only be implemented after the comprehensive testing of UAV operations in these specific mountain environments. Full article

Unmanned aerial vehicles (UAVs) are becoming a major part of the civil and military aviation industries. They meet user needs for effective supply transportation and the real-time acquisition of accurate information during air operations. Recently, concerns about greenhouse gas (GHG) emissions have increased due to the use and depletion of fossil fuels, shifting attention toward the broader use of electric propulsion as a green technology in different sectors, including transportation. The long-term objective of this work is to build a prototype of a hybrid electric propulsion system (HEPS) dedicated to a multi-rotor unmanned aerial vehicle with a MTOW of 25 kg and an onboard electric voltage of 44.4 V. The main components and operating principles of the HEPS were defined. The main HEPS digital twin block modules and their operations were described. Using the developed digital twin structure and operational model, simulations were carried out. Based on the results, it can be demonstrated that the use of hybrid electric propulsion allows for a significant increase in the flight time of a multi-rotor UAV. The developed DT can be used as a tool for optimizing the operation of the HEPS prototype and for redefining mathematical models of individual components. Full article

Military operators performing vehicle maintenance work are at times subject to onerous tasks such as lifting and transporting heavy loads, potentially in confined spaces. As this presents a risk for developing musculoskeletal injury, it is of interest to evaluate if a passive back-support exosuit could help reduce back muscle load. This study used wireless electromyographic (EMG) sensors to evaluate the biomechanical effects of exosuits during lifting tasks. Ten male participants performed military-relevant lifting tasks with and without wearing the exosuit in randomised orders. The lifting tasks included (1) vertical lifts of different weights (15 and 25 kg) onto different platform heights (0.5 m and 1.2 m) and (2) a lateral walk task across 4 m in a confined space while carrying a 39 kg weight. EMG activities of three back muscle groups (longissimus, iliocostalis, and multifidus) were measured and normalised to maximal isometric back extension tasks. The results showed no significant differences in muscle activation between conditions in most lifting tasks, except for a reduction in longissimus muscle activity when using the exosuit during lateral walking. Individual responses varied substantially, with some participants showing reduced muscle activity, while others did not. These findings highlight the challenges in implementing exosuits in reducing back muscle load during military lifting tasks. While passive back-support exosuits may provide benefits to some users, their effectiveness varies among individuals and may be task-dependent. Full article

Unmanned aerial vehicle (UAV) swarms are widely applied in various fields, including military and civilian domains. However, due to the scarcity of spectrum resources, UAV swarm clustering technology has emerged as an effective method for achieving spectrum sharing among UAV swarms. This paper introduces a distributed heterogeneous multi-agent deep reinforcement learning algorithm, named HMDRL-UC, which is specifically designed to address the cluster-based spectrum sharing problem in heterogeneous UAV swarms. Heterogeneous UAV swarms consist of two types of UAVs: cluster head (CH) and cluster member (CM). Each UAV is equipped with an intelligent agent to execute the deep reinforcement learning (DRL) algorithm. Correspondingly, the HMDRL-UC consists of two parts: multi-agent proximal policy optimization for cluster head (MAPPO-H) and independent proximal policy optimization for cluster member (IPPO-M). The MAPPO-H enables the CHs to decide cluster selection and moving position, while CMs utilize IPPO-M to cluster autonomously under the condition of certain partial channel distribution information (CDI). Adequate experimental evidence has confirmed that the HMDRL-UC algorithm proposed in this paper is not only capable of managing dynamic drone swarm scenarios in the presence of partial CDI, but also has a clear advantage over the other existing three algorithms in terms of average throughput, intra-cluster communication delay, and minimum signal-to-noise ratio (SNR). Full article

With its unique environment and strategic value, the near space (NS) has become the focus of global scientific and technological, military, and commercial fields. Aiming at the problem of communication interruption when the aircraft re-enters the atmosphere, to ensure the needs of communication, navigation, and telemetry, tracking, and command (TT&C), this paper proposes an overall integration of communication, navigation, and TT&C (ICNT) signals scheme based on the K/Ka frequency band. Firstly, the K/Ka frequency band is selected according to the ITU frequency division, high-speed communication requirements, advantages of space-based over-the-horizon relay, overcoming the blackout problem, and the development trend of high frequencies. Secondly, the influence of the physical characteristics of the NS on ICNT is analyzed through simulation. The results show that when the K/Ka signal is transmitted in the NS, the path loss changes significantly with the elevation angle. The bottom layer loss at an elevation angle of 90° is between 143.5 and 150.5 dB, and the top layer loss is between 157.5 and 164.4 dB; the maximum attenuation of the bottom layer and the top layer at an elevation angle of 0° is close to 180 dB and 187 dB, respectively. In terms of rainfall attenuation, when a 30 GHz signal passes through a 100 km rain area under moderate rain conditions, the horizontal and vertical polarization losses reach 225 dB and 185 dB, respectively, and the rainfall attenuation increases with the increase in frequency. For gas absorption, the loss of water vapor is higher than that of oxygen molecules; when a 30 GHz signal is transmitted for 100 km, the loss of water vapor is 17 dB, while that of oxygen is 2 dB. The loss of clouds and fog is relatively small, less than 1 dB. Increasing the frequency and the antenna elevation angle can reduce the atmospheric scintillation. In addition, factors such as the plasma sheath and multipath also affect the signal propagation. In terms of modulation technology, the constant envelope signal shows an advantage in spectral efficiency; the new integrated signal obtained by integrating communication, navigation, and TT&C signals into a single K/Ka frequency point has excellent characteristics in the simulation of power spectral density (PSD) and autocorrelation function (ACF), verifying the feasibility of the scheme. The proposed ICNT scheme is expected to provide an innovative solution example for the communication, navigation, and TT&C requirements of NS vehicles during the re-entry phase. Full article

Unmanned aerial vehicle networks (UAVNs) are widely used to collect various location-related data, with applications ranging from military reconnaissance to the low-altitude economy. Data security and privacy are critical concerns when outsourcing location-related data to a public cloud. To alleviate these concerns, location-related data are encrypted before outsourcing to the public cloud. However, encryption decreases the operability of the outsourced encrypted data; thus, unmanned aerial vehicles cannot operate on the encrypted data directly. Among operations on encrypted location-related data, the forward-secure range query is one of the most fundamental operations. In this paper, we present a forward-secure range query based on spatial division to achieve a highly efficient range query on encrypted location-related data while preserving both data security and privacy. Specifically, various space-filling curves were experimentally investigated for both the range query and the k-nearest-neighbor query. Then, a forward-secure range query (namely, OSFC-FSQ) was constructed on an encrypted dual dictionary. The proposed scheme was evaluated on real-world datasets, and the results show that it outperforms state-of-the-art schemes in terms of accuracy and query time in the cloud. Full article