High-altitude Unmanned Aerial Vehicles Research Articles

Numerical investigation on effects of low Reynolds number conditions on fan shaped film cooling performances

This study investigates the effects of low Reynolds number (Re) conditions on the cooling performance of fan-shaped film cooling holes in the gas turbine engines of high-altitude long-endurance Unmanned Aerial Vehicles (UAVs). The significance of film cooling technology becomes paramount due to the low Re operational environment of UAVs. A novel Very Large Eddy Simulation (VLES) method was employed to systematically analyze a range of mainstream Reynolds numbers (ReD) from 480 to 32 000 and blowing ratios (M) from 1.0 to 2.5 while keeping the density ratio (DR) constant at 1.75. Compared to other turbulence models, the VLES model showed the highest similarity in predicting thermal field distributions and the most accurate prediction of film cooling performance at low Re. The results reveal that at low ReD, significant flow concentration within the hole leads to reduced velocity uniformity at the outlet, resulting in poor film coverage downstream. Additionally, the coolant jet tends to detach from the wall, adversely affecting cooling performance. In contrast, higher ReD exhibited improved coolant jet adhesion to the wall and cooling efficiency, attributed to the reduced intensity of counter-rotating vortex pair and decreased hot gas entrainment, thereby enhancing cooling effectiveness. Notably, for the same ReD values, cases with M = 1.5 consistently showed better cooling effectiveness compared to other M conditions. This study provides new insight into the cooling performance of fan-shaped film cooling holes under low Reynolds number conditions, which is crucial for enhancing the cooling efficiency of gas turbines in high-altitude UAVs.

Accurate Detection and Tracking of Small-Scale Vehicles in High-Altitude Unmanned Aerial Vehicle Bird-View Imagery

Vehicle detection and tracking from unmanned aerial vehicles (UAVs) aerial images are among the main tasks of intelligent traffic systems. Especially in tasks with long distances, extensive backgrounds, and small objects, it increases the difficulty of localization and regression, which can easily lead to missed detections and false positives. This paper proposes a detection-based small-scale vehicle tracking framework that integrates an improved YOLOX network and the DeepSORT algorithm to address these issues. Based on the original YOLOX network, a shallow feature extraction network, 160 × 160 pixels, is added to enhance the ability to extract small-scale object features. A convolutional block attention module (CBAM) is inserted in front of the neck network to select crucial information for vehicle detection tasks while suppressing noncritical ones. EIoU_Loss is introduced as the bounding box regression loss function in training to speed up their convergence and improve the localization accuracy of the small objects. Furthermore, an image segmentation method is proposed to effectively reduce missed and false detection events. It divides the original high-definition image into multiple subimages, first detected and then reassembled. Finally, the improved YOLOX network is used as the detector of the DeepSORT to perform small-scale vehicle detection and tracking tasks in various traffic scenarios. Experiments show that the proposed method can significantly improve the detection accuracy of the network and effectively solve the problems of missed detection and false positives in small-scale vehicle tracking tasks in high-resolution aerial images captured by high-altitude UAVs. Significantly, the algorithm proposed in this paper has sufficient robustness for small-scale tracking tasks of aerial videos captured at different altitudes.

UAV Dynamic Non-Terrestrial Transmission Channel Analysis Based on SSCM-RT Model

Unmanned Aerial Vehicles (UAVs) have become crucial components of building air–ground integrated networks for sixth-generation mobile communications. UAV-related technology has advanced quickly in both military and civilian contexts. Problems with long-distance and dynamic communication need to be fixed in the non-terrestrial transmission channels of high-altitude UAVs. For long-distance UAV dynamic non-terrestrial transmission channel modeling, a spatial statistical channel model–ray tracing (SSCM-RT) hybrid channel model is proposed and verified, and SSCM-RT channel simulations incorporating spatial consistency analysis are carried out to realize the description of the communication process in the dynamic scenario of the non-terrestrial transmission in symmetric and asymmetric situations. The SSCM-RT model can output channel state information continuously, which is helpful for the quantitative description and characterization of the UAV channel in practical settings.

An Innovative Heat Rejection System for High Altitude Unmanned Aerial Vehicles

An Innovative Heat Rejection System for High Altitude Unmanned Aerial Vehicles

Using Semicircular Sampling to Increase Sea-Wind Retrieval Altitude with a High-Altitude UAV Scatterometer

Currently, unmanned aerial vehicles (UAVs) are widely used due to their low cost and flexibility. In particular, they are used in remote sensing as airborne platforms for various instruments. Here, we investigate the capability of a conical scanning radar operated as a scatterometer mounted on a high-altitude UAV to perform sea surface wind retrieval based on an appropriate geophysical model function (GMF). Increasing the maximum altitude of the wind retrieval method’s applicability is an important problem for UAV or manned aircraft scatterometers. For this purpose, we consider the possibility of increasing the method’s maximum altitude by applying a semicircular scheme for azimuth normalized radar cross section (NRCS) sampling instead of a whole 360° circular scheme. We developed wind retrieval algorithms for both semicircular and circular NRCS sampling schemes and evaluated them using Monte Carlo simulations. The simulations showed that the semicircular scheme for azimuth NRCS sampling enables twice the maximum altitude for wind retrieval compared to a 360° circular scheme. At the same time, however, the semicircular scheme requires approximately three times the number of integrated NRCS samples in each azimuth sector to provide equivalent wind retrieval accuracy. Nonetheless, our results confirm that the semicircular azimuth NRCS sampling scheme is well-suited for wind retrieval, and any wind retrieval errors are within the typical range for scatterometer wind recovery. The obtained results can be used for enhancing existing UAV and aircraft radars, and for the development of new remote sensing systems.

An efficient backbone network for target detection in aerial images

Target detection in aerial images by high altitude unmanned aerial vehicles is one of the hot research topics. A detection that is efficient and accurate is of a high value in the military and civilian fields. However, due to the irregular distribution of targets and their various scales shown in aerial images, it is difficult for existing backbone networks to effectively extract target features based on deep learning. To address these problems, in the paper, an efficient backbone network called AerNet is proposed, to which a local feature enhancement module (LFEM) is added to fully extract discriminative features of aerial targets via multi-scale convolutional layers. The network AerNet consists of 55 layers, which can keep high spatial resolution in deeper layers and maintain a large receptive field. Experimental results show that our AerNet has achieved a satisfying detection performance on the DOTA benchmark.

Determining an Improved Traffic Conflict Indicator for Highway Safety Estimation Based on Vehicle Trajectory Data

Currently, several traffic conflict indicators are used as surrogate safety measures. Each indicator has its own advantages, limitations, and suitability. There are only a few studies focusing on fixed object conflicts of highway safety estimation using traffic conflict technique. This study investigated which conflict indicator was more suitable for traffic safety estimation based on conflict-accident Pearson correlation analysis. First, a high-altitude unmanned aerial vehicle was used to collect multiple continuous high-precision videos of the Jinan-Qingdao highway. The vehicle trajectory data outputted from recognition of the videos were used to acquire conflict data following the procedure for each conflict indicator. Then, an improved indicator Ti was proposed based on the advantages and limitations of the conventional indicators. This indicator contained definitions and calculation for three types of traffic conflicts (rear-end, lane change and with fixed object). Then the conflict-accident correlation analysis of TTC (Time to Collision)/PET (Post Encroachment Time)/DRAC (Deceleration Rate to Avoid Crash)/Ti indicators were carried out. The results show that the average value of the correlation coefficient for each indicator with different thresholds are 0.670 for TTC, 0.669 for PET, and 0.710 for DRAC, and 0.771 for Ti, which Ti indicator is obviously higher than the other three conventional indicators. The findings of this study suggest TTC often fails to identify lane change conflicts, PET indicator easily misjudges some rear-end conflict when the speed of the following vehicle is slower than the leading vehicle, and PET is less informative than other indicators. At the same time, these conventional indicators do not consider the vehicle-fixed objects conflicts. The improved Ti can overcome these shortcomings; thus, Ti has the highest correlation. More data are needed to verify and support the study.

Communication Aware UAV Swarm Surveillance Based on Hierarchical Architecture

Multi-agent unmanned aerial vehicle (UAV) teaming becomes an essential part in science mission, modern warfare surveillance, and disaster rescuing. This paper proposes a decentralized UAV swarm persistent monitoring strategy in realizing continuous sensing coverage and network service. A two-layer (high altitude and low altitude) UAV teaming hierarchical structure is adopted in realizing the accurate object tracking in the area of interest (AOI). By introducing the UAV communication channel model in its path planning, both centralized and decentralized control schemes would be evaluated in the waypoint tracking simulation. The UAV swarm network service and object tracking are measured by metrics of communication link quality and waypoints tracking accuracy. UAV swarm network connectivity are evaluated over different aspects, such as stability and volatility. The comparison of proposed algorithms is presented with simulations. The result shows that the decentralized scheme outperforms the centralized scheme in the mission of persistent surveillance, especially on maintaining the stability of inner UAV swarm network while tracking moving objects.

Massive MIMO for Cellular-Connected UAV: Challenges and Promising Solutions

Massive multiple-input multiple-output (MIMO) is a promising technology for enabling cellu-lar-connected unmanned aerial vehicle (UAV) communications in the future. Equipped with full-dimensional large arrays, ground base stations (GBSs) can apply adaptive fine-grained 3D beamforming to mitigate the strong interference between high-altitude UAVs and low-altitude terrestrial users, thus significantly enhancing the network spectral efficiency. However, the performance gain of massive MIMO critically depends on accurate channel state information of both UAVs and terrestrial users at the GBSs, which is practically difficult to achieve due to UAV-in-duced pilot contamination and UAVs' high mobility in 3D. Moreover, the increasingly popular applications relying on a large group of coordinated UAVs or UAV swarm as well as the practical hybrid GBS beamforming architecture for massive MIMO further complicate the pilot contamination and channel/beam tracking problems. In this article, we provide an overview of the above challenging issues, propose new solutions to cope with them, and discuss promising directions for future research. Preliminary simulation results are also provided to validate the effectiveness of the proposed solutions.

Approaches to the analysis and synthesis of unmanned aircraft system in the research task of aerial survey of area object

The presented research was performed to develop a scientific and methodological apparatus for estimation of aerial survey effectiveness. The work takes into account the parameters of the unmanned aerial vehicle, of the optoelectronic onboard special complex and the spatial properties of the areal object. The result of the research of works in the field of aerial survey using unmanned aerial systems is presented. It is revealed that the analysis and synthesis of specific sets of unmanned aerial vehicles with onboard special complexes is carried out in a qualitative way according to individual technical parameters. At the same time, aggregate indicators characterizing aerial survey effectiveness are not evaluated. Models of an unmanned aerial vehicle, special airborne complex, areal object and requirements for the quality of survey materials are proposed. The assumptions under which the modeling of aerial survey of the areal object is performed are determined. On the basis of models the procedures of analysis and synthesis of aerial survey system are developed. The content of the procedures takes into account the loss of the survey resource that occurs due to the remoteness of the object and making approaches to the next shooting route in tack flight mode. The procedures allow to determine the potential effectiveness of the survey and to choose the configuration of the onboard special complex to ensure optimal performance of the survey of the areal object. The results of a computational experiment on the example of a conditionally real light high-altitude unmanned aerial vehicle are presented. The dependence of the effectiveness of aerial photography on the remoteness and spatial properties of the areal object is presented. For different conditions, the configuration of the onboard special complex, which provide optimal multi-route shooting, is determined.

Sizing of a Turboprop Engine Powered High Altitude Unmanned Aerial Vehicle and It`s Propulsion System for an Assumed Mission Profile in Turkey

In this study, preliminary sizing of a turboprop engine powered high altitude unmanned aerial vehicle and it`s propulsion system for an assumed mission profile in Turkey was performed. Aircraft mission profile is one of the most important design inputs in aircraft design. While the aircraft is dimensioned according to the requirements in the specification (useful payload, range, target cost, etc.), parameters such as cruise altitude and speed within the mission profile affect the engine type, power level, fuel quantity, and therefore the overall dimensions and total weight of the aircraft. The unmanned aerial vehicle with turboprop engine investigated in this study, can stay in the air for at least 24 hours at high altitude (40000 ft) and can be used for border surveillance, coast control, forest fires and land exploration.

Pilot Decontamination for Massive MIMO Network With UAVs

This letter studies the pilot contamination (PC) problem for massive multiple-input multiple-output (MIMO) networks with coexisting terrestrial users and unmanned aerial vehicles (UAVs). Due to the strong line-of-sight (LoS) air-to-ground channels between UAVs and base stations (BSs), UAVs usually cause a more severe PC issue as compared to the traditional terrestrial users. To mitigate the PC caused by UAVs, we propose a low-complexity distributed scheme by exploiting the full-dimensional beamforming of massive MIMO BSs and the angle-dependent LoS channels between them and high-altitude UAVs. Numerical results show the effectiveness of the proposed pilot decontamination scheme and the significant signal-to-interference-plus-noise ratio (SINR) gains in both the uplink and downlink after pilot decontamination.

Flat-upper-surface wing for experimental high altitude unmanned aerial vehicle

Technology of photovoltaic cells and lithium batteries is developing rapidly. As a result, more and more attempts are made to build solar high altitude long endurance airplanes. Unfortunately, data on altitude impact on photovoltaic cells and batteries performance are not easily available. Moreover, acquisition cost of cells is still high. As a result, high altitude long endurance airplanes design is expensive and risky. Therefore, a tool for inexpensive testing of cells is needed. A small and very light unmanned aerial vehicle can be used for this purpose. It could fly as high as the envisaged high altitude long endurance airplane with a small number of cells and batteries, providing valuable information on them. The weight of such an experimental unmanned aerial vehicle could be minimized because long endurance would not be required, so heavy load of lithium batteries could be minimized, reducing also weights of other components. Wings of this unmanned aerial vehicle should enable installation of various types of photovoltaic cells including rigid ones. Therefore, it would be advantageous to apply an airfoil with a flat-upper-surface as large as possible. Unfortunately, flat-upper-surface airfoils are not popular in airfoils catalogs. Therefore, an attempt was undertaken to design an airfoil with 75% flat upper surface. The research focused on maximization of the lift-to-drag ratio and power factor assuming low Reynolds numbers conditions since it was designed for a small unmanned aerial vehicle for photovoltaic cells testing. This paper contains description of design methodology, design assumptions, and the obtained results. Moreover, the authors describe the experiment undertaken to verify the design. The wind tunnel and a semi-span model used for this experiment are presented together with the obtained results. The model has a similar structure to the envisaged structure of unmanned aerial vehicle, so flexibility of the wing is taken into account.

Aerodynamic Model-Aided Estimation of Attitude, 3-D Wind, Airspeed, AOA, and SSA for High-Altitude Long-Endurance UAV

This article proposes a novel dynamic model-aided navigation filter to estimate the safety-critical states of an aircraft including the effect of wind. Aerodynamic coefficients and control signals are used to predict the angular rates. Experimental flight results of a high-altitude long-endurance unmanned aerial vehicle (UAV) demonstrated improvement in attitude estimation compared to a model-based navigation algorithm that does not consider wind, as well as accurate attitude estimation without using gyroscope signals, demonstrating its effectiveness for analytical redundancy.

Advanced “Confident Judgments” Method when Choosing Multicriteria Solutions in a Multipurpose Approach

The article considers the problem of making multicriteria decisions in which the decision maker (DM) has the opportunity to indicate the range of selection policies to determine the most effective scope of the considered alternatives. The concept of the Dirichlet area of an alternative is introduced in the blurred area of the target settings of the DM, and four groups of quantitative characteristics are proposed for a holistic description of these areas. A six-step decision-making algorithm is developed. Two mathematical models of multipurpose optimization and systematization of selection policies in the Dirichlet domain are proposed. The proposed method is illustrated by solving the problem of choosing the complex of the most rational concepts of a high-altitude unmanned aerial vehicle.

Hierarchical Collaboration Approach for Tracking of Flying Target by UAVs

This paper investigates a hierarchical target tracking method based on the collaboration of unmanned aerial vehicles (UAVs) at different altitudes. To enhance the target tracking range, the high-altitude UAVs monitor the wide area, and transmit their surveillance information to low-altitude UAVs which directly detect and collect information about the target's movements. The contributions of this paper are threefold: First, to track the flying target in a dynamic environment, a modified Lyapunov guidance vector field (LGVF) method is used to plan velocities for UAVs, where a time-varying vertical component is incorporated into the traditional LGVF function to satisfy the constraints of cluster communication. Secondly, a three-dimensional local collision-free guidance vector field (TLCGVF) method is proposed for UAVs to plan collision-free paths on line. To simultaneously track the target and avoid obstacles, the vector field by LGVF is used as the original vector field of TLCGVF. Thirdly, the rolling optimization strategy is used to adjust the reactive parameters of TLCGVF to enhance the path quality. The simulation results confirm the feasibility of the above approach.

SIZING OF A TURBOPROP ENGINE POWERED HIGH ALTITUDE UNMANNED AERIAL VEHICLE AND IT`S PROPULSION SYSTEM FOR AN ASSUMED MISSION PROFILE IN TURKEY

ABSTRACT In this study, preliminary sizing of a turboprop engine powered high altitude unmanned aerial vehicle and it`s propulsion system for an assumed mission profile in Turkey was performed. Aircraft mission profile is one of the most important design inputs in aircraft design. While the aircraft is dimensioned according to the requirements in the specification (useful payload, range, target cost, etc.), parameters such as cruise altitude and speed within the mission profile affect the engine type, power level, fuel quantity, and therefore the overall dimensions and total weight of the aircraft. The unmanned aerial vehicle with turboprop engine investigated in this study, can stay in the air for at least 24 hours at high altitude (40000 ft) and can be used for border surveillance, coast control, forest fires and land exploration.

Trajectory Optimization for High-Altitude Long-Endurance UAV Maritime Radar Surveillance

For an unmanned aerial vehicle (UAV) carrying out a maritime radar surveillance mission, there is a tradeoff between maximizing information obtained from the search area and minimizing fuel consumption. This article presents an approach for the optimization of a UAV's trajectory for maritime radar wide area persistent surveillance to simultaneously minimize fuel consumption, maximize mean probability of detection, and minimize mean revisit time. Quintic polynomials are used to generate UAV trajectories due to their ability to provide complete and complex solutions while requiring few inputs. Furthermore, the UAV dynamics and surveillance mission requirements are used to ensure that a trajectory is realistic and mission compatible. A wide area search radar model is used within this article in conjunction with a discretized grid in order to determine the search area's mean probability of detection and mean revisit time. The trajectory generation method is then used in conjunction with a multiobjective particle swarm optimization algorithm to obtain a global optimum in terms of path, airspeed (and thus time), and altitude. The performance of the approach is then tested over two common maritime surveillance scenarios and compared to an industry recommended baseline.

Multi-objective optimisation of semi-closed cycle engines for high-altitude UAV propulsion

ABSTRACTThe maximum attainable performance of small gas turbines represents a strong limitation to the operating altitude and endurance of high-altitude unmanned aerial vehicles (UAVs). Significant improvement of the cycle thermal efficiency can be achieved through the introduction of heat exchangers, with the consequent increase of the overall engine weight. Since semi-closed cycle engines can achieve a superior degree of compactness compared to their open cycle counterparts, their use can offset the additional weight of the heat exchangers. This paper applies semi-closed cycles to a high-altitude UAV propulsion system, with the objective of assessing the benefits introduced on the engine performance and weight. A detailed model has been created to account for component performance and size variation as function of thermodynamic parameters. The sizing has been coupled with a multi-objective optimisation algorithm for minimum specific fuel consumption and weight. Results of two different semi-closed cycle configurations are compared with equivalent state-of-the-art open cycles, represented by a recuperated and an intercooled-recuperated engine. The results show that, for a fixed design power output, engine weight is approximately halved compared to state-of-the-art open cycles, with slightly improved specific fuel consumption performance. Optimum semi-closed cycles furthermore operate at higher overall pressure ratios than open cycles and make use of recuperators with higher effectiveness as the mass penalty of the recuperator is smaller due to the lower engine mass flow rates.

Network-Connected UAV: 3-D System Modeling and Coverage Performance Analysis

With growing popularity, unmanned aerial vehicles (UAVs) are pivotally extending conventional terrestrial Internet of Things (IoT) into the sky. To enable high-performance two-way communications of UAVs with their ground pilots/users, cellular network-connected UAV has drawn significant interests recently. Among others, an important issue is whether the existing cellular network, designed mainly for terrestrial users, is also able to effectively cover the new UAV users in the three-dimensional (3D) space for both uplink and downlink communications. Such 3D coverage analysis is challenging due to the unique air-ground channel characteristics, the resulted interference issue with terrestrial communication, and the non-uniform 3D antenna gain pattern of ground base station (GBS) in practice. Particularly, high-altitude UAV often possesses a high probability of line-of-sight (LoS) channels with a large number of GBSs, while their random binary (LoS/Non-LoS) channel states and (on/off) activities give rise to exponentially large number of discrete UAV-GBS association/interference states, rendering coverage analysis more difficult. This paper presents a new 3D system model to incorporate UAV users and proposes an analytical framework to characterize their uplink/downlink 3D coverage performance. To tackle the above exponential complexity, we introduce a generalized Poisson multinomial (GPM) distribution to model the discrete interference states, and a novel lattice approximation (LA) technique to approximate the non-lattice GPM variable and obtain the interference distribution efficiently with high accuracy. The 3D coverage analysis is validated by extensive numerical results, which also show effects of key system parameters such as cell loading factor, GBS antenna downtilt, UAV altitude and antenna beamwidth.