Unmanned Air Systems Research Articles

ANALYSIS OF APPLICATION POSSIBILITIES AND CLASSIFICATION OF UNMANNED AERIAL VEHICLES FOR THE SUPPORT OF COMBAT OPERATIONS OF THE NAVY OF THE ARMED FORCES OF UKRAINE

Nowadays, in the course of war between Ukraine and the russian federation, there is a large-scale employ of various weapon systems that are used on land, in the air, and at sea. Unlike the enemy, Ukraine Forces prefer to utilize asynchronous methods of armed struggle. In order to successfully implementation of these asynchronous methods is necessary used to contemporary unmanned aerial vehicles and unmanned air systems. It is known that at the beginning phase of the war the Ukrainian defenders were used unmanned aerial vehicles and unmanned air systems on the principle of “controlled chaos”. As a result of these active operations, the Ukrainian defenders could discourage and defeat enemy. Therefore, in order to secure effective usage of unmanned aerial vehicles and unmanned air systems it is necessary to introduce a clear hierarchy with clear classification features. This task is certainly relevant today for Ukrainian NAVY. It is the significant task, because the Ukrainian NAVY has some experience in the combat use of unmanned aerial vehicles and unmanned air systems, but they need its systematization and comprehensive implementation, taking into account the specifics of conducting combat operations at Black sea. At the same time, in order to improve functionality and effectiveness of the unmanned aerial vehicles and unmanned air systems the developers must apply information technologies such as, internet of military things, cloud technologies and artificial intelligence. For instance, if developers wanted to implementation of internet of military things technologies, they would be able to ensure intercommunication among different groups of aerial vehicles and simplify to control process of them.
 In the proposed paper, the authors tried to perform capabilities analysis of usage of different types unmanned aerial vehicles and unmanned air systems with various control systems and military categories based on the use of NATO standards. In addition, the authors performed this analysis considering different types Ukrainian NAVY ships and support vessels. Moreover, the authors of the paper also proposed a classification for unmanned aerial vehicles of Ukrainian NAVY.

Design, Selection, and Evaluation of Reinforcement Learning Single Agents for Ground Target Tracking

Previous approaches for small fixed-wing unmanned air systems that carry strapdown rather than gimbaled cameras achieved satisfactory ground target tracking performance using both standard and deep reinforcement learning algorithms. However, these approaches have significant restrictions and abstractions to the dynamics of the vehicle, such as constant airspeed and constant altitude, because the number of states and actions was necessarily limited. Thus, extensive tuning was required to obtain good tracking performance. The expansion from 4 state–action degrees of freedom to 15 enabled the agent to exploit previous reward functions that produced novel yet undesirable emergent behavior. This paper investigates the causes of and various potential solutions to undesirable emergent behavior in the ground target tracking problem. A combination of changes to the environment, reward structure, action space simplification, command rate, and controller implementation provides insight into obtaining stable tracking results. Consideration is given to reward structure selection and refinement to mitigate undesirable emergent behavior. Results presented in the paper for a simulated environment of a single unmanned air system tracking a randomly moving single ground target show that a soft actor–critic algorithm can produce feasible tracking trajectories without limiting the state space and action space, provided that the environment is properly posed.

System Identification of Unmanned Air Systems at Texas A&M University

This paper presents a summary of system identification flight testing and results for a variety of large and small fixed-wing and multirotor unmanned air systems at Texas A&M University from 1999 to 2023. The six different types of vehicles range from a large powered parafoil, to a fixed-wing vehicle with synthetic jet-actuated roll control effectors, to a radially asymmetric multirotor, to large and small fixed-wing vehicles, and to a Steppe eagle. The observer/Kalman filter identification algorithm is used to generate linear time-invariant state-space models, and the results for both near-real-time online model generation and postflight offline model generation are presented. The use and efficacy of a variety of test input types and their sensitivity to exogenous inputs such as turbulence, in addition to identified model evaluation and selection criteria, are discussed. Several generations of low size, weight, power, and cost flight-test instrumentation including the Developmental Flight-Test Instrumentation data acquisition package are also presented. Challenges that arose from the flight-testing campaigns along with solutions are highlighted in the paper.

A Bayesian track management scheme for improved multi‐target tracking and classification in drone surveillance radar

AbstractIn this article, a simple, yet effective, Bayesian scheme for tracks maintenance, promotion, and deletion in drone surveillance radar is presented. It enables the simultaneous tracking of the target body and micro‐Doppler components that originate from the motion of rotors (if any) onboard an unmanned air system. This not only delivers more accurate multi‐target tracking, but also substantially improves the radar automatic target classification capability (e.g. discriminating between drone and non‐drone targets). Challenging and diverse real staring radar datasets are used here to demonstrate the efficacy and benefits of the proposed track management approach.

Control Acquisition Attack of Aerospace Systems via False Data Injection

The cyber threat to aerospace systems has been growing rapidly in recent years with several real-world and experimental cyberattacks observed. This growing threat has prompted investigation of cyberattack and defense strategies for manned and unmanned air systems, spacecraft, and other aerospace systems. The work in this paper seeks to further understand these attacks by introducing and developing a novel cyberattack for autonomous aerospace systems. The problem faced by the attacker is posed and discussed analytically using false data injection of state measurements to exploit the vehicle’s onboard controller to take control of the system. It is shown that the attacker can utilize traditional control techniques to exert control over the system and eliminate the control of the victim by intercepting and modifying the vehicle’s measurement data. The attacker is able to accomplish this objective without any prior knowledge of the system’s plant, controller, or reference signal. The attack is demonstrated on the elevator-to-pitch-attitude-angle dynamics of a Cessna T-37 aircraft model. It is shown to be successful in eliminating the victim’s control influence over the system and driving the system to its own target state.

Trends in Uav Platforms and Technologies

Unmanned Air Vehicles (UAVs) have developed into indispensable war fighting assets of modern battlefield. UAVs play a pivotal role in sharing and disseminating strategic information in a Network-centric war scenario. The fusion of the data obtained from different sensors/ payloads further helps enhance situational awareness and enables quicker sensor-to-shooter reactions. There is a marked shift in the importance given to the Unmanned Air Systems development world-wide with significant increases in budget allocations. From Micro Air Vehicles (MAVs) to Unmanned Combat Aircraft, each type of UAV plays a distinct role at the same time presenting unique technological challenges. The paper discusses the present state of, and future trends in, various UAV platforms as well as sensor payloads carried by them and also highlights challenges in the related technologies. It also describes the ongoing UAV programs and technology competence built up by DRDO.

Deterministic and Probabilistic Approaches to Model and Update Dynamic Systems

Updating simulation models, based on flight test or other data, or creating a model using only experimental data is a necessary process that can be costly and laborious. Simulation updates are necessary for high-fidelity simulations used in analysis, control development, handling qualities prediction, fleet training, etc. This paper presents methods to update aircraft models based on deterministic and probabilistic approaches. The deterministic approach is based on a collection of signal processing, statistical analysis, and maximum likelihood estimators embodied in the Algorithms to Update Simulation Parameters with Experimental Data tool. Mathematically sound and statistically rigorous techniques are used to calculate updates of current model parameters and suggest new terms capturing unmodeled dynamics, thereby improving correlation with observed vehicle response. The probabilistic approach is based on generalized polynomial chaos theory included in the Algorithms for Uncertainty Representation and Analysis (AURA) tool. The AURA tool allows the user to update probabilistic models based on experimental data, formulated as a Bayesian inference problem. This paper will present the methodology for both deterministic and probabilistic approaches and provide examples of their application to different aircraft designs, including tilt-rotor and rotary-wing unmanned air system vehicles. The results for both deterministic and probabilistic modeling approaches demonstrate excellent results. The probabilistic approach is novel in its expressive power to propagate and update probabilistic models and provides users with an intuitive and powerful modeling approach.

Application of unmanned air systems in agriculture

The purpose of this article is to consider the use of unmanned aerial systems (UAS) in agriculture. UAVs have great potential in many agricultural tasks. This article summarizes the current state of drone technology and its applications in agriculture, including plant health monitoring, weed control, spraying, and other agricultural operations.

Detection of Low RCS Unmanned Air Systems Using K-Band Continuous Wave Doppler Radar

UASs (Unmanned Air Systems) are universally used in many activities, spanning from leisure-commercial to military applications. Accordingly, as the number of UASs operating in the sky increases, so does the need to detect and identify them, in order to ensure their legitimate use. This paper introduces a continuous wave (CW) Doppler radar implementation that can be used to provide early warning for flying-by small UASs. By applying Fast Fourier Transform (FFT) to the returned signal’s Doppler frequency, estimations can be made regarding the presence of aerial bodies inside an Area of Interest (AoI). Achieving reliable detection with a low false alarm rate (FAR) while keeping the size and power demands of the system to minimum was a challenge that was successfully met. The proposed system was extensively tested in outdoor environments; measurement results are presented and parameters such as radar power, antenna gain, and noise are discussed.

Sidelobe Suppression Techniques for Near-Field Multistatic SAR

Multirotor Unmanned Air Systems (UAS) represent a significant improvement in capability for Synthetic Aperture Radar (SAR) imaging when compared to traditional, fixed-wing, platforms. In particular, a swarm of UAS can generate significant measurement diversity through variation of spatial and frequency collections across an array of sensors. In such imaging schemes, the image formation step is challenging due to strong extended sidelobe; however, were this to be effectively managed, a dramatic increase in image quality is theoretically possible. Since 2015, QinetiQ have developed the RIBI system, which uses multiple UAS to perform short-range multistatic collections, and this requires novel near-field processing to mitigate the high sidelobes observed and form actionable imagery. This paper applies a number of algorithms to assess image reconstruction of simulated near-field multistatic SAR with an aim to suppress sidelobes observed in the RIBI system, investigating techniques including traditional SAR processing, regularised linear regression, compressive sensing. In these simulations presented, Elastic net, Orthogonal Matched Pursuit, and Iterative Hard Thresholding all show the ability to suppress sidelobes while preserving accuracy of scatterer RCS. This has also lead to a novel processing approach for reconstructing SAR images based on the observed Elastic net and Iterative Hard Thresholding performance, mitigating weaknesses to generate an improved combined approach. The relative strengths and weaknesses of the algorithms are discussed, as well as their application to more complex real-world imagery.

Application of UAS for Monitoring of Forest Ecosystems

In the last couple of years, there have been a great number of articles that cover and emphasize the advantages and possibilities that UAS (Unmanned Air System) offers in forest ecosystem research. In the available research, alongside UAS, the importance of developing sensors that are designed to be used with UAV (Unamnned Air Vehicle), a flight programming software and UAS collected data processing software have been pointed out. With the widespread use of high-precision sensors and accompanying software in forestry, it is possible to obtain accurate data in a short time that replaces long-term manpower in the field with equal or in some cases, such as windthrow calculation or wildlife counting, greater accuracy. The former practice of manual imagery processing is being partly replaced with automated approaches. The paper analyses studies that deal with some form of application of UAS in forestry, e.g. forest inventory, forest operations, ecological monitoring, forest pests and forest fires, and wildlife monitoring. In the forest inventory, a large number of studies deal with the possibilities of applying UAS in mapping vegetation and individual trees, morphological research of individual parts of trees, surface analysis, etc. The use of remote and proximal sensing technologies in forest engineering has mainly been focused on defining surface roughness and topology, road geometry, planning and maintenance, ground-based and cable-based harvesting and soil characteristics and displacement. Wildfire monitoring already relies heavily on the use of UAS and thermal cameras in operations, and it is similar to the mapping of windthrow or directions of the spread of certain insects important for forestry. In wildlife research, numerous studies deal with abundance research of individual terrestrial birds and mammals using UAS thermal imagery. With some drawbacks such as wildlife disturbance or limited UAV range, common to most of the processed studies are positive attitudes regarding the application of UAS in forestry sensing and monitoring, which is slowly becoming a common operative practice, with the scientists’ focus being on developing automated approaches in UAS imagery processing. Reducing the error by improving the technological characteristics of the sensors will in the long run reduce the number of people required to collect data important for forestry, reduce risks and in some cases increase accuracy.

Unmanned air systems (UAS/UAV) (drone) and aerial mobility: summaries of the 2018 and 2020 TQA workshops

Unmanned air system (UAS/UAV) noise and urban mobility noise were the subject of two National Academy of Engineering (NAE) hosted workshops under the auspices of the Technology of Quieter America (TQA) program. Both workshops were organized by the INCE Foundation in cooperation with the U.S. National Aeronautics and Space Administration (NASA) and the U.S. Federal Aviation Administration (FAA). The first workshop "UAS and UAV (Drone): Noise Emissions and Noise Control Engineering Technology" was held in Washington, DC in December, 2018. manufacturers, users, U.S. government agencies, universities, consultants and professional societies. The second was an e-workshop "Aerial Mobility: Noise Issues and Technology" in December, 2020. Participants at each workshop included representatives from manufacturers (US and international), users, U.S. government agencies, academia, consultants, professional societies, and law firms. Topics included: modelling, testing, psychoacoustics, community impact, noise reduction strategies, measurement techniques, and uses of both UAS/UAVs and aerial mobility.

Carbon fiber reinforced Zn–MnO2 structural composite batteries

Structural composite batteries, which can simultaneously carry mechanical loads and store electric energy, have the potential to significantly reduce the system weight of electric-powered systems including electric cars, unmanned air systems, and mobile robots. Recent research in this area has primarily focused on carbon-fiber based lithium-ion batteries, which require stringent protection against factors such as toxicity, moisture, and overheating, making it particularly challenging to realize the potential of structural batteries. Herein, we propose a novel carbon fiber reinforced Zn–MnO2 structural composite battery featuring a MnO2 cathode and a zinc ion anode; carbon fibers conduct current and provide stiffness and strength. The resulting structural Zn–MnO2 composite battery, which can be manufactured using a simple vacuum consolidation process, without the need for inert gloveboxes, demonstrates an excellent tensile strength of 293 MPa and a high specific capacity of 145.9 mAh g−1. Moreover, the structural composite battery achieves an excellent energy density of 181.5 Wh kg−1 and retains 88.3% capacity after 100 cycles. The new carbon fiber Zn–MnO2 structural composite battery offers huge potential for next-generation energy-storing structures that are safe, eco-efficient, and provide multifunctional performance.

Efficient Estimation of Probability of Conflict Between Air Traffic Using Subset Simulation

This paper presents an efficient method for estimating the probability of conflict between air traffic within a block of airspace. Autonomous sense-and-avoid is an essential safety feature to enable unmanned air systems to operate alongside other (manned or unmanned) air traffic. The ability to estimate the probability of conflict between traffic is an essential part of sense-and-avoid. Such probabilities are typically very low. Evaluating low probabilities using naive direct Monte Carlo generates a significant computational load. This paper applies a technique called subset simulation. The small failure probabilities are computed as a product of larger conditional failure probabilities, reducing the computational load while improving the accuracy of the probability estimates. The reduction in the number of samples required can be one or more orders of magnitude. The utility of the approach is demonstrated by modeling a series of conflicting and potentially conflicting scenarios based on the standard Rules of the Air.

Development of Technology for Remote Location of Unknown Underground Cavities and Deep-Seated Rockslides by Unmanned Air Systems (UAS)

This work aims to create new scientific knowledge by developing new innovative technology for remote detection of unknown underground cavities and deep-seated rockslides. To achieve the goal, we intend to develop new innovative technology for remote localization of unknown underground cavities and deep-seated rockslides using a thermal camera mounted on a unmanned aerial vehicle (UAV).Technology is a defined sequence of operations and procedures under optimal conditions, varying within certain allowable limits, resulting in obtaining a particular result or product that meets certain requirements. Therefore, the development of new technology involves determining the allowable limits of deviation of the optimal conditions of operations and procedures for producing a good result that meets the established requirements. The development of new technology also involves determining the limits of its applicability under different external conditions. This paper includes determination of the allowable limits and the limits of applicability of the new technology being developed.Until now, no technology has been developed for remote detection of unknown underground cavities or deep-seated rockslides. The goal of this work is the development of such innovative technology with numerous applications in construction, environmental studies and protection, security, defence and infrastructure.

Investigation of Micro Gas Turbine Systems for High Speed Long Loiter Tactical Unmanned Air Systems

In this study, the on-going research into the improvement of micro-gas turbine propulsion system performance and the suitability for its application as propulsion systems for small tactical UAVs (<600 kg) is investigated. The study is focused around the concept of converting existing micro turbojet engines into turbofans with the use of a continuously variable gearbox, thus maintaining a single spool configuration and relative design simplicity. This is an effort to reduce the initial engine development cost, whilst improving the propulsive performance. The BMT 120 KS micro turbojet engine is selected for the performance evaluation of the conversion process using the gas turbine performance software GasTurb13. The preliminary design of a matched low-pressure compressor (LPC) for the proposed engine is then performed using meanline calculation methods. According to the analysis that is carried out, an improvement in the converted micro gas turbine engine performance, in terms of thrust and specific fuel consumption is achieved. Furthermore, with the introduction of a CVT gearbox, the fan speed operation may be adjusted independently of the core, allowing an increased thrust generation or better fuel consumption. This therefore enables a wider gamut of operating conditions and enhances the performance and scope of the tactical UAV.

Modeling of upset sensor operation for autonomous unmanned systems applications

PurposeThe purpose of this paper is to develop and implement a general sensor model under normal and abnormal operational conditions including nine functional categories (FCs) to provide additional tools for the design, testing and evaluation of unmanned aerial systems within the West Virginia University unmanned air systems (UAS) simulation environment.Design/methodology/approachThe characteristics under normal and abnormal operation of various types of sensors typically used for UAS control are classified within nine FCs. A general and comprehensive framework for sensor modeling is defined as a sequential alteration of the exact value of the measurand corresponding to each FC. Simple mathematical and logical algorithms are used in this process. Each FC is characterized by several parameters, which may be maintained constant or may vary during simulation. The user has maximum flexibility in selecting values for the parameters within and outside sensor design ranges. These values can be set to change at pre-defined moments, such that permanent and intermittent scenarios can be simulated. Sensor outputs are integrated with the autonomous flight simulation allowing for evaluation and analysis of control laws.FindingsThe developed sensor model can provide the desirable levels of realism necessary for assessing UAS behavior and dynamic response under sensor failure conditions, as well as evaluating the performance of autonomous flight control laws.Research limitations/implicationsDue to its generality and flexibility, the proposed sensor model allows detailed insight into the dynamic implications of sensor functionality on the performance of control algorithms. It may open new directions for investigating the synergistic interactions between sensors and control systems and lead to improvements in both areas.Practical implicationsThe implementation of the proposed sensor model provides a valuable and flexible simulation tool that can support system design for safety purposes. Specifically, it can address directly the analysis and design of fault tolerant flight control laws for autonomous UASs. The proposed model can be easily customized to be used for different complex dynamic systems.Originality/valueIn this paper, information on sensor functionality is fused and organized to develop a general and comprehensive framework for sensor modeling at normal and abnormal operational conditions. The implementation of the proposed approach enhances significantly the capability of the UAS simulation environment to address important issues related to the design of control laws with high performance and desirable robustness for safety purposes.

A design framework for realizing multifunctional wings for flapping wing air vehicles using solar cells

Long flight durations are highly desirable to expand mission capabilities for unmanned air systems and autonomous applications in particular. Flapping wing aerial vehicles are unmanned air system platforms offering several performance advantages over fixed wing and rotorcraft platforms, but are unable to reach comparable flight times when powered by batteries. One solution to this problem has been to integrate energy harvesting technologies in components, such as wings. To this end, a framework for designing flapping wing aerial vehicle using multifunctional wings using solar cells is described. This framework consists of: (1) modeling solar energy harvesting while flying, (2) determining the number of solar cells that meet flight power requirements, and (3) determining appropriate locations to accommodate the desired number of solar cells. A system model for flapping flight was also developed to predict payload capacity for carrying batteries to provide energy only for power spikes and to enable time-to-land safely in an area where batteries can recharge when the sun sets. The design framework was applied to a case study using flexible high-efficiency (>24%) solar cells on a flapping wing aerial vehicle platform, known as Robo Raven IIIv5, with the caveat that a powertrain with 81% efficiency is used in place of the current servos. A key finding was the fraction of solar flux incident on the wings during flapping was 0.63 at the lowest solar altitude. Using a 1.25 safety factor, the lowest value for the purposes of design will be 0.51. Wind tunnel measurements and aerodynamic modeling of the platform determined integrating solar cells in the wings resulted in a loss of thrust and greater drag, but the resulting payload capacity was unaffected because of a higher lift coefficient. A time-to-land of 2500 s was predicted, and the flight capability of the platform was validated in a netted test facility.

Suction control of flow separation of a low-aspect-ratio wing at a low Reynolds number

Suction-based flow control is explored as one of means of enhancing the performance of a low aspect ratio (AR) wing. Large-eddy simulation (LES) was performed to investigate the flow past a three-dimensional (3D) NACA0012 profile wing tip at a chord-based Reynolds number of 35966, such configurations and flow conditions are typical of those utilized in a small unmanned air system (UAS). The flow separation appears at an angle of attack a = 15°, which is used as the example for our investigation. After validating of our numerical results, the suction distribution was designed and mounted near the wing root, and two different control parameters, suction coefficients and angles, were investigated to assess the benefits of flow control and to determine their effectiveness. Our results show that suction control can improve the lift, and the suction coefficient has larger effect on the aerodynamic performances of the wing than that of the suction angle. The lift enhancement is attributed to the standing vortex near the leading edge and the trajectory of wing tip vortex is also affected during the suction control.

Exploring tandem wing UAS designs for operation in turbulent urban environments

The stability of small unmanned air systems can be challenged by turbulence during low-altitude flight in cluttered urban environments. This paper explores the benefits of a tandem wing aircraft configuration with the implementation of a pressure-based phase-advanced turbulence sensory system on a small unmanned air system for gust mitigation. The objective was to utilise passive and active methods to minimise gust-induced perturbations. Experimentation in repeatable turbulence within a wind tunnel’s test section was conducted. The experiments focus on the roll axis, which is isolated through a specially designed roll-axis rig. The results show improvement over conventional aircraft. This work is part of a larger research project aimed at enabling safe, stable and steady small unmanned air systems flight in urban environments.