Search Results (153)

To address the challenges of complex low-altitude flight environments for UAVs, where numerous obstacles often lead to GPS signal obstruction and multipath effects, this study proposes an integrated inertial navigation and GPS positioning approach for coordinated cross-path planning in drone swarms. The methodology involves the following: (1) discretizing continuous 3D airspace into grid cells using occupancy grid mapping to construct an environmental model; (2) analyzing dynamic flight characteristics through attitude angle variations in a 3D Cartesian coordinate system; and (3) implementing collaborative state updates and global positioning through fused inertial–GPS navigation. By incorporating Cramér–Rao lower bound optimization, the system achieves effective cross-path planning for drone formations. Experimental results demonstrate a 98.35% mission success rate with inter-drone navigation time differences maintained below 0.5 s, confirming the method’s effectiveness in enabling synchronized swarm operations while maintaining safe distances during cooperative monitoring and low-altitude flight missions. This approach demonstrates significant advantages in coordinated cross-path planning for UAV clusters. Full article

The aviation sector significantly contributes to environmental challenges, including global warming and greenhouse gas emissions, due to its reliance on fossil fuels. Fuel cells present a viable alternative to conventional propulsion systems. In the context of light aircraft applications, proton exchange membrane fuel cells (PEMFCs) have recently attracted growing interest as a substitute for internal combustion engines (ICEs). However, their performance is highly sensitive to altitude variations, primarily due to limitations in compressor efficiency and instability in cathode pressure. To address these challenges, this research presents a comprehensive numerical model that couples a PEMFC system with a dynamic air compressor model under altitude-dependent conditions ranging from 0 to 3000 m. Iso-efficiency lines were integrated into the compressor map to evaluate its behavior across varying environmental parameters. The study examines key fuel cell stack characteristics, including voltage, current, and net power output. The results indicate that, as altitude increases, ambient pressure and air density decrease, causing the compressor to work harder to maintain the required compression ratio at the cathode of the fuel cell module. This research provides a detailed prediction of compressor efficiency trends by implementing iso-efficiency lines into the compressor map, contributing to sustainable aviation and aligning with global goals for low-emission energy systems by supporting cleaner propulsion technologies for lightweight aircraft. Full article

As urban populations expand and congestion intensifies, traditional ground transportation struggles to satisfy escalating mobility demands. Unmanned Electric Vertical Take-Off and Landing (eVTOL) aircraft, as a key enabler of Urban Air Mobility (UAM), leverage low-altitude airspace to alleviate ground traffic while offering environmentally sustainable solutions. However, supporting high bandwidth, real-time video applications, such as Virtual Reality (VR), Augmented Reality (AR), and 360° streaming, remains a major challenge, particularly within bandwidth-constrained metropolitan regions. This study proposes a novel Unmanned Aerial Vehicle (UAV)-enabled video streaming architecture that integrates 6G wireless technologies with intelligent routing strategies across cooperative airborne nodes, including unmanned eVTOLs and High-Altitude Platform Systems (HAPS). By relaying video data from low-congestion ground base stations to high-demand urban zones via autonomous aerial relays, the proposed system enhances spectrum utilization and improves streaming stability. Simulation results validate the framework’s capability to support immersive media applications in next-generation autonomous air mobility systems, aligning with the vision of scalable, resilient 3D transportation infrastructure. Full article

Unmanned aerial vehicles (UAVs), owing to their flexible coverage expansion and dynamic adjustment capabilities, hold significant application potential across various fields. With the emergence of urban low-altitude air traffic dominated by UAVs, the integrated aviation information network combining UAVs and manned aircraft has evolved into a complex space–air–ground integrated Internet of Things (IoT) system. The application of 5G/6G network technologies, such as cloud computing, network function virtualization (NFV), and edge computing, has enhanced the flexibility of air traffic services based on service function chains (SFCs), while simultaneously expanding the network attack surface. Compared to traditional networks, the aviation information network integrating UAVs exhibits greater heterogeneity and demands higher service reliability. To address the failure issues of SFCs under attack, this study proposes an efficient SFC recovery method for recovery rate optimization (ERRRO) based on virtual network functions (VNFs) migration technology. The method first determines the recovery order of failed SFCs according to their recovery costs, prioritizing the restoration of SFCs with the lowest costs. Next, the migration priorities of the failed VNFs are ranked based on their neighborhood certainty, with the VNFs exhibiting the highest neighborhood certainty being migrated first. Finally, the destination nodes for migrating the failed VNFs are determined by comprehensively considering attributes such as the instantiated SFC paths, delay of physical platforms, and residual resources. Experiments demonstrate that the ERRRO performs well under networks with varying resource redundancy and different types of attacks. Compared to methods reported in the literature, the ERRRO achieves superior performance in terms of the SFC recovery rate and delay. Full article

To study the influence of speed brake deflection on remote sensing grayscale images and the radar cross section (RCS) of aircraft, we present a comprehensive method based on remote sensing modeling and dynamic electromagnetic scattering. The results indicate that grayscale images from ground remote sensing can capture the hierarchical information of various reference objects and water bodies. When the target aircraft enters the observation area, complex ground reference objects may blur the grayscale features of the speed brake. The RCS of the speed brake shows strong dynamic characteristics under the example of the forward azimuth, where the maximum variation can reach 43.433 dBm². When the speed brakes on both sides dynamically deflect, the aircraft’s RCS in the lateral azimuth will fluctuate significantly in the first half of the observation time, and those in the forward and backward azimuths will show clear dynamic characteristics in the second half of the observation time. Low grayscale ground reference and water body boundaries/areas are beneficial for distinguishing the deflection of the deceleration plate. The comprehensive method proposed here is effective for studying remote sensing grayscale images and the dynamic RCS of aircraft under speed brake deflection. Full article

To advance the hydrogen energy-driven low-altitude aviation sector, it is imperative to establish sophisticated risk assessment frameworks tailored for hydrogen-powered aircraft. Such methodologies will deliver fundamental guidelines for the preliminary design phase of onboard hydrogen systems by leveraging rigorous risk quantification and scenario-based analytical models to ensure operational safety and regulatory compliance. In this context, this study proposes a comprehensive hazard and operability analysis-fuzzy dynamic Bayesian network (HAZOP-FDBN) framework, which quantifies risk without relying on historical data. This framework systematically maps the risk factor relationships identified in HAZOP results into a dynamic Bayesian network (DBN) graphical structure, showcasing the risk propagation paths between subsystems. Expert knowledge is processed using a similarity aggregation method to generate fuzzy probabilities, which are then integrated into the FDBN model to construct a risk factor relationship network. A case study on low-altitude aircraft hydrogen storage systems demonstrates the framework’s ability to (1) visualize time-dependent failure propagation mechanisms through bidirectional probabilistic reasoning, and (2) quantify likelihood distributions of system-level risks triggered by component failures. Results validate the predictive capability of the model in capturing emergent risk patterns arising from subsystem interactions under low-altitude operational constraints, thereby providing critical support for safety design optimization in the absence of historical failure data. Full article

Background: The aim of the study was to assess retinal circulation in military pilots, as well as to determine the relationship between the type of aircraft, flight altitude, total hours of flight time and parameters of retinal circulation, using OCT angiography (OCT-A). Methods: This cross-sectional study enrolled 44 military pilots and 44 controls. The inclusion criteria encompassed healthy adult men. Due to the fact that military pilots cannot suffer from any vision defects or any other eye disease, the exclusion criteria concerned the control group and included refractive error exceeding −3 diopters (D) and +3 D and concomitant eye diseases, such as any retinal or choroidal pathologies, glaucoma, uveitis. The exclusion criteria for both groups were low-quality OCT-A images. Subsequently, the results of the measurements obtained for 176 eyes were included in further descriptive and multivariate analyses, of which 88 were in the pilot group versus 88 in the comparison group. Results: The total vessel density in superficial and deep capillary plexuses was significantly decreased (p = 0.0176, p < 0.0001, resp.) the longer the flight experience, particularly in the parafoveal region (p = 0.0299 and p < 0.0001, resp.). Moreover, the foveal avascular zone area was significantly increased proportionally to the total hours of flight (p = 0.0083). Also, the total vessel density was increased with a higher flight altitude in the deep capillary plexus (p = 0.0042), especially in the parafoveal region (p = 0.0110). Conclusions: Gravitational forces manifesting in the unique conditions of the flight of military pilots seem to induce microvascular changes in the retina. Full article

The power to weight ratio of power plants is an important consideration, especially in the design of Unmanned Aircraft System (UAS). In this paper, a UAS with an MTOW of 35.3 kg, equipped with a fuel cell as a prime power supply to provide electrical power to the propulsion system, is considered. A pressure vessel design that can estimate and determine the total size and weight of the combined power plant of a fuel cell stack with hydrogen and air/oxygen vessels and the propulsion system of the UAS for high-altitude operation is proposed. Two scenarios are adopted to determine the size and weight of the pressure vessels required to supply oxygen to the fuel cell stack. Different types of stainless-steel materials are used in the design of the pressure vessel in order to find an appropriate material that provides low size and weight advantages. Also, the design of a hydrogen pressure vessel and mass estimation are also considered. The estimated sizes and weights of the hydrogen and oxygen vessels of the power plant and propulsion system in this research offer a maximum of four hours of flying time for the UAS mission; this is based on a Horizon (H-1000) Proton Exchange Membrane (PEM) stack. Full article

The growing use of quadrotor unmanned aerial vehicles (UAVs), especially in low-altitude airspace, has raised concerns about their susceptibility to high-intensity radiated fields (HIRFs). These electromagnetic interferences can significantly affect UAV performance and safety. Therefore, understanding the electromagnetic behavior of quadrotor UAVs in HIRF environments and establishing robust airworthiness standards is crucial. In this paper, a novel transfer function model specifically designed for small quadrotor UAVs in HIRF environments is studied, covering the frequency range from 100 MHz to 6 GHz. The model characterizes the relationship between internal electric field strength and frequency in response to external excitation conditions. A comprehensive simulation of the interference with UAVs in the HIRF environment is conducted, followed by test validation in an anechoic chamber. To assess the consistency between simulation and test results, the feature selection validation (FSV) method is employed. This paper also compares the UAV transfer function with that of a conventional aircraft, revealing the unique electromagnetic characteristics of quadrotor UAVs and offering insights into their vulnerability in HIRF environments. The findings provide valuable contributions to the development of UAV airworthiness certification standards and their safe operation in complex electromagnetic environments. Full article

To address the deficiency of aircraft point cloud training data for low-altitude environment perception systems, a method termed APCG (aircraft point cloud generation) is proposed. APCG can generate aircraft point cloud data in the single photon counting Lidar (SPC-Lidar) system based on information such as aircraft type, position, and attitude. The core of APCG is the aircraft depth image generator, which is obtained through adversarial training of an improved conditional generative adversarial network (cGAN). The training data of the improved cGAN are composed of aircraft depth images formed by spatial sampling and transformation of fine point clouds of 76 types of aircraft and 4 types of drone. The experimental results demonstrate that APCG is capable of efficiently generating diverse aircraft point clouds that reflect the acquisition characteristics of the SPC-Lidar system. The generated point clouds exhibit high similarity to the standard point clouds. Furthermore, APCG shows robust adaptability and stability in response to the variation in aircraft slant range. Full article

Considering the principles of green and low-carbon development, practitioners strive to continuously improve propeller performance as a primary goal for propeller-powered aircraft. Specially, medium and high-altitude UAVs require propellers that possess sufficient thrust and high efficiency across the entire flight envelope to improve the UAV’s endurance and mission capability. However, given the constraints imposed by flight altitude, speed, and power system capacity, attaining optimal matching of rotational speed and torque for fixed-pitch propellers across different operating scenarios remains a significant challenge. To ensure optimal aerodynamic performance across diverse design points, variable pitch technology is adopted, and a multi-objective propeller optimization design method is proposed that adapts to the varying pitch angle strategy. Based on the standard strip analysis, with different profile chord lengths and twist angle distributions of the propeller blade as the control parameters, we establish a multi-objective propeller aerodynamic shape optimization model using a genetic optimization algorithm. The newly designed electrically variable pitch propeller, employing this method, exhibits good aerodynamic performance throughout the flight envelope. Its design has been validated through high-precision CFD analysis and wind tunnel testing, achieving a cruising efficiency of up to 84.5%. The results show that the propeller performance calculation has good consistency with the test and can meet the requirements of unmanned aircraft. Full article

A short takeoff and vertical landing unmanned aerial vehicle (STOVL UAV) is significantly influenced by factors such as the ship’s surface effect, deck motion, and jet effect during vertical landing on an aircraft carrier. The existing control logic cannot effectively solve the coupling problem of longitudinal attitude and trajectory, so it is hard to guarantee the stability and control accuracy of the UAV at low speed. To address the aforementioned interference and coupling problems, a comprehensive control law based on a radial basis function neural network (RBFNN) and nonlinear dynamic optimal allocation is designed in this paper. Firstly, the integrated landing control law of the STOVL UAV is designed. Considering the model uncertainty and complex landing environment, an RBFNN is used for online observation and compensation to improve the robustness of the system. Subsequently, a dynamic control allocation module based on nonlinear optimization is developed to simultaneously satisfy force and moment commands. The simulation results show that the integrated control method effectively decouples the pitch attitude and longitudinal trajectory at low speeds, resulting in effective convergence control of pitch angle, forward flight speed, and altitude. The integration of the RBFNN, as evaluated by the integral of absolute error (IAE), results in a 93% improvement in control accuracy compared to the integrated landing control law designed in this paper without the RBFNN integration. Full article

With the rapid expansion of urban populations and the accelerated pace of urbanization, the concept of urban air mobility (UAM) has emerged. During flights, UAM aircraft need to transmit real-time sensing information to base stations for further processing and analysis. Large-scale real-time data require leveraging the computing capabilities of edge servers at the network edge to reduce transmission delay and energy consumption of UAM aircraft. In cases where edge servers are unable to process information, an unmanned aerial vehicle (UAV) equipped with computing capabilities and operating in low-altitude airspace can serve as a relay to assist in communication and computation. Due to the limited payloads and flight times of UAVs and UAM aircraft, delay and energy consumption within the system pose significant challenges. To tackle these challenges, two fundamental objectives have been proposed: minimizing delay and minimizing energy consumption. Furthermore, an optimization problem has been proposed to minimize the weighted sum of delay and energy consumption. Then, a UAM federated twin delayed deep deterministic policy gradient (UF-TD3) algorithm has been proposed to solve the original problems characterized by complex, non-convex, and inseparable variables. Simulation results show that the proposed UF-TD3 algorithm converges quickly and significantly outperforms four other baseline algorithms in optimizing delay and energy consumption performance. Moreover, compared to the conventional delay minimization strategy and energy minimization strategy, the proposed strategy of minimizing the weighted sum of delay and energy consumption can reduce the delay by 63.8% and reduce energy by 73.96%. Full article

Freezing rain and freezing drizzle can produce nearly undetectable hazards, with potentially catastrophic consequences for aircraft within low altitudes (e.g., the terminal area). However, the lack of direct observations of the low-altitude freezing precipitation environment creates a challenge for forecasters, flight crews, dispatchers, and air traffic controllers. This research demonstrates how unmanned aerial vehicles (UAVs) can be designed and instrumented to create unmanned aerial weather measurement systems (WxUAS) capable of characterizing the low-altitude freezing precipitation environment and providing insight into the mechanisms that govern it. In this article, we discuss the design considerations for WxUAS-based in situ sampling during active precipitation. We present results from controlled experiments at the Oklahoma Mesonet’s calibration laboratory as well as results from intercomparison studies with collocated well-established ground-based instruments in Oklahoma and Colorado. Additionally, we explore the insights provided by high-resolution thermodynamic and cloud droplet size distribution profiles and their potential contributions to a better understanding of the low-altitude freezing precipitation environment. Full article

High-altitude relight is a critical challenge for aero-engines, directly impacting the safety and emergency response capabilities of aircraft. This paper systematically reviews the physical mechanisms, key factors, and relevant prediction models of high-altitude relight, highlighting the detrimental effects of extreme conditions such as low pressure and temperature on fuel evaporation rates, flame propagation speeds, and turbulent combustion processes. A comprehensive overview of the current state of high-altitude relight research is presented, alongside recommendations for enhancing the ignition performance of aero-engines under extreme conditions. This paper focuses on the development of ignition prediction models, including early empirical and semi-empirical models, as well as physics-based models for turbulent flame propagation and flame kernel tracking, assessing their applicability in high-altitude relight scenarios. Although flame kernel tracking has shown satisfactory performance in predicting ignition probability, it still overly relies on manually set parameters and lacks precise descriptions of the physical processes of flame kernel generation. Future studies on some topics, including refining flame kernel modeling, strengthening the integration of experimental data and numerical simulations, and exploring the incorporation of new ignition technologies, are needed, to further improve model reliability and predictive capability. Full article