Unmanned Aerial Systems Operations Research Articles

On the importance of continuous development in the military domain

A significant percentage of modern products and systems purchased from the defense industry are difficult for the buyer to adapt or develop for new needs after lessons learned on the battlefield. This results in the procured systems having unnecessarily short lifespans. This paper contains a literature survey of the implementation and adaptation of military systems, combined with the authors’ own observations from real cases of procurement in the military domain. Furthermore,this paper presents concepts for continuous development in the military domain, addressing several of the issues observed with modern systems. The term “continuous development” is here defined as the continuous modification, improvement and enhancement of military equipment or a military technical system over the course of its life cycle. The paper outlines how compatibility, flexibility and interoperability relate to unmanned aerial vehicles, counter unmanned aerial systems operations and electronic warfare operations, their role in continuous development and why these concepts are important on the modern battlefield. We contend that the ability to modify equipment increases adaptability, and therefore survivability, in conflict scenarios where new threats continuously appear. The paper concludes with recommendations of practical value for the defense industry on how equipment can be adapted to facilitate continuous development.

Enabling Technologies for the Navigation and Communication of UAS Operating in the Context of BVLOS

Unmanned Aerial Systems (UAS) have rapidly gained attraction in recent years as a promising solution to revolutionize numerous applications and meet the growing demand for efficient and timely delivery services due to their highly automated operation framework. Beyond Visual Line of Sight (BVLOS) operations, in particular, offer new means of delivering added-value services via a wide range of applications. This "plateau of productivity" holds enormous promise, but it is challenging to equip the drone with affordable technologies which support the BVLOS use case. To close this gap, this work showcases the convergence of the automotive and aviation industries to advance BVLOS aviation for UAS in a practical setting by studying a combination of Commercial Off-The-Shelf (COTS) technologies and systems. A novel risk-based approach of investigating the key technological components, architectures, algorithms, and protocols is proposed that facilitate highly reliable and autonomous BVLOS operations, aiming to enhance the alignment between market and operational needs and to better identify integration requirements between the different capabilities to be developed.

Human Performance in Highly Automated, Cyber Vulnerable Unmanned Aerial Systems: Effects of Operators’ Background and Task Load

This article evaluated the effects of operator background and task load on operator ability to detect and respond to cyber events while controlling multiple unmanned aerial systems (UAS). Cyber physical systems (CPS) are susceptible to cyber threats and associated events via connections critical to their operations. The effects of cyber intrusions on UAS operator performance as a function of background and task load have been understudied. Fifty-one operators with different backgrounds (Aviators, Gamers and Non-Gamers; n = 17 per group) were evaluated across two levels of task load (in-the-loop (ITL) and out-of-the-loop (OTL)) while controlling a simulation of multiple UAS involving cyber events. Cyber events represented spoofed information that could not be corroborated with available secondary information/displays. Multivariate analysis of variance was used to analyze the effect of background and task load on operator performance, subjective perception of workload (assessed using the NASA Task Load Index), and trust. Nongamers responded to cyber events 62.8% and 67.7% slower than aviators and gamers, respectively. Mean response times across task load conditions were substantially longer for cyber events (128.9 s) than for noncyber, “real” events (42.8 s). Scenario type (ITL/OTL) was statistically significant for workload, cyber classification, and cyber action response. The findings may inform recruitment criteria for future UAS operators. Individuals with gaming experience may be as adept at responding to cyber events while operating multiple UAS as aviators. Cyber events are likely to affect the performance of the overall CPS due to their impact on the human operator.

Acoustic non-destructive testing of UAS´s propellers during predeparture and post-flight checks

Unmanned Aerial System (UAS) activities have increased steeply in the last years, market research forecasts a continuous increase in the near future. The rapid growth of this industry, however, has outpaced the development of rules and systems to govern their use, as well as those to ensure a safe operation before, during and after flight. Maintenance, Repair and Overhaul (MRO) aspects will gain relevance as more and more UAS take to the sky. Rotary-wing UAS have 2 or more propellers, which are easily damaged during normal operation of the vehicle. The reduced thrust and increased vibration imply losing performance and setting the UAS structure under stress. With the propellers being the main source of sound of the propulsion system, we propose the use of acoustics to identify damaged propellers. Microphones placed off-board do neither disrupt UAS operation nor reduce the payload capacity. Furthermore, this method does not depend on a particular manufacturer or software. In this paper, we present a concept for the non-destructive testing of multi-copter propellers. The fault diagnosis aims at recognizing the difference in sound between damaged and undamaged propellers. This evaluation takes place before the UAS takes off the ground and after it lands, thus allowing to interrupt a possible dangerous mission or identifying damage occurred during operation. The vehicle is on the ground in an “idle state” where the propellers already spin, but not fast enough to lift it. This state is used for a first analysis of the sound of a single propeller and several propellers, as well as for the generation of data. Next, two approaches for the detection of damage are developed and their performance is evaluated: an analytical approach and a machine learning algorithm based on an autoencoder neural network....

Flight Test Analysis of UTM Conflict Detection Based on a Network Remote ID Using a Random Forest Algorithm

In an area where unmanned aerial system (UAS) traffic is high, a conflict detection system is one of the important components for the safety of UAS operations. A novel UAS traffic management (UTM) monitoring application was developed, including a conflict detection system using the inverted teardrop area detection based on real-time flight data transmitted from the network remote identification (Remote ID) modules. This research aimed to analyze the performance of the UTM-monitoring application based on flight test data using statistical and machine learning approaches. The flight tests were conducted using several types of small fixed-wing unmanned aerial vehicles (UAVs) controlled by a human pilot using a Taiwan cellular communication network in suburban and rural areas. Two types of scenarios that involved a stationary, on-the-ground intruder and a flying intruder were used to simulate a conflict event. Besides the statistical method calculating the mean and standard deviation, the random forest algorithm, including regressor and classifier modules, was used to analyze the flight parameters and timing parameters of the flight tests. The result indicates that the processing time of the UTM application was the most significant parameter to the conflict warning parameter, besides the relative distance and height between UAVs. In addition, the latency time was higher for the flight in the rural area than the suburban area and also higher for data transmitted from the flying position than the ground position. The findings of our study can be used as a reference for aviation authorities and other stakeholders in the development of future UTM systems.

Modeling Public Concerns for Unmanned Aerial System Operations in the National Airspace System

The Unites States commercial unmanned aerial system (UAS) market was valued at $99.6 million in 2020 and is projected to reach $3.7 billion by 2030. Applications for these commercial UAS range from risk mitigation and surveillance to package delivery. Coupled with these emerging applications are the unique factors that arise with a commercial UAS’s compact size and low-altitude flights among the civilian populace. In this work, a value model was created to attempt to aid in determining the infringement of a UAS operation configuration on a civilian environment. Value functions were developed in an additive model that measures infringement (a UAS’s encroachment or trespass on a right or privilege of a civilian) based on these attributes. The resulting value model was tested by running 100,000 random simulations. Analysis of the simulation results and sensitivity analysis of the model showed that fleet size, proximity, duration of the operation within a certain proximity, and total operation duration were the attributes that drove a UAS operation’s infringement on an environment. A use case of an Amazon delivery application was then examined. This is a realistic scenario simulated to study if duration of an operation and time near a structure are kept to a minimum, the infringement of an operation remained low. This study provides initial determination of how infringement of UAS can be quantified and what infringement values may look like for different operational scenarios.

Learning Sensor Based Risk Map Augmentation for Risk Aware UAS Operation

Unmanned Aerial Systems (UAS) have become increasingly popular and have been identified as a good platform for a range of tasks from surveillance and inspection to delivery and maintenance. In many of these applications these systems have to operate in environments that are frequented by people or that contain sensitive infrastructure and in which the operation of UAS thus poses physical risk in terms of damage in case of vehicle failure or psychological or privacy risks which would make their operation less acceptable. To increase the use of these systems it is thus important that they can take into account these risks when determining navigation strategies. While this can sometimes be done based on prior information, such as street and building plans in cities, a priori information is often not complete, making it essential that risk representations can be augmented in real time based on sensor information. This paper presents an approach to risk map augmentation that uses learned risk identification from aerial pictures to fuse additional information with prior data into a dynamically changing risk map that allows effective re-planning of navigation strategies.

Strategies for Passing Regulatory Procedures during the Operational Phase of Unmanned Aircraft Systems

The problem of integration of unmanned aerial systems (UAS) into the airspace of the Russian Federation is currently receiving increased attention. The conceptual proposals under development define the main directions of regulatory and technological policy for the integration of UAS into the airspace of the Russian Federation, as well as the effective airspace use (AU) by all users in the interests of national security and economic development of the Russian Federation. The issues of regulation in the field of UAS application in the Russian Federation, in this regard, are of particular relevance. This article analyzes the main possible strategies for passing regulatory procedures at the stage of UAS operation. On the basis of this analysis, the strategies for the commercial application of UAS are formulated.

Aerodynamic optimization and analysis of quadrotor blades operating in the Martian atmosphere

The design of unmanned aerial systems (UAS) for flight in the Martian atmosphere is a relevant and current topic. The successful flight of the Ingenuity helicopter recently proved its applicability. We present a numerical approach to the aerodynamic optimization of blades for rotors working in flow regimes with Reynolds numbers smaller than 15,000. Due to the atmospheric gas density and viscosity on Mars and the required rotation speed and rotor diameter, rotary-wing works mainly in the so-called ultra-low Reynolds number regime (103<Re<104), where the flow is likely laminar. The tip region is in the lower range of the very-low Reynolds number regime (104<Re<105), where separation-induced laminar-turbulent transition may occur. Such conditions characterize rotor blades of UAS operating in the Martian atmosphere or at very high altitudes (30 km) in the Earth's atmosphere. The blade design procedure consists of a two-step optimization process. The process starts with an initial two-dimensional airfoil design analysis followed by three-dimensional Blade Element Momentum (BEM) simulations to achieve the chord and twist radial distributions necessary to define the blade geometry. Then, a procedure to perform three-dimensional adjoint-based CFD simulations enhances the performance. The aerodynamic characteristics of optimal blades are evaluated with Navier-Stokes (N-S) and Large Eddy Simulations (LES), demonstrating the negligible effect of turbulence in blade performance for these Reynolds numbers when the boundary layer is attached. The implemented BEM method and high-fidelity CFD simulations show a good agreement.

Autonomous UAS-Based Agriculture Applications: General Overview and Relevant European Case Studies

Emerging precision agriculture techniques rely on the frequent collection of high-quality data which can be acquired efficiently by unmanned aerial systems (UAS). The main obstacle for wider adoption of this technology is related to UAS operational costs. The path forward requires a high degree of autonomy and integration of the UAS and other cyber physical systems on the farm into a common Farm Management System (FMS) to facilitate the use of big data and artificial intelligence (AI) techniques for decision support. Such a solution has been implemented in the EU project AFarCloud (Aggregated Farming in the Cloud). The regulation of UAS operations is another important factor that impacts the adoption rate of agricultural UAS. An analysis of the new European UAS regulations relevant for autonomous operation is included. Autonomous UAS operation through the AFarCloud FMS solution has been demonstrated at several test farms in multiple European countries. Novel applications have been developed, such as the retrieval of data from remote field sensors using UAS and in situ measurements using dedicated UAS payloads designed for physical contact with the environment. The main findings include that (1) autonomous UAS operation in the agricultural sector is feasible once the regulations allow this; (2) the UAS should be integrated with the FMS and include autonomous data processing and charging functionality to offer a practical solution; and (3) several applications beyond just asset monitoring are relevant for the UAS and will help to justify the cost of this equipment.

Numerical studies on modeling the near- and far-field wake vortex of a quadrotor in forward flight

The operation of Unmanned Aerial Systems (UAS) is expected to keep increasing in the future with its rapid advancement and ever-expanding applications. One of the safety measures that need to be put into place for safe UAS operations is separation requirements. This article presents the results from flow simulations of quadrotor propellers using the Overset method in ANSYS Fluent 19.2 and the Virtual Blade Model (VBM) method in OpenFOAM as part of ongoing work to establish a wake vortex–based safe separation distance for UAS operations. The near-field flow simulation using the Reynolds-averaged Navier–Stokes turbulence model was validated with mesh convergence and turbulence model studies and verified with simulation and experimental data in the literature to ensure that the propeller simulation methods could generate a realistic near-field flow of multi-rotor UAS in forward flight. The far-field flow simulation using the Large Eddy Simulation turbulence model was validated with a mesh convergence study by calculating and comparing the circulation strength of the vortices in the far-field flow of each mesh setup but not verified due to a lack of existing experimental data.

Unmanned aerial systems: Status and Forthcoming challenges for Safety Risk Management

Urban Air Mobility (UAM) promises a revolution in urban transportation: for the first time ever, cities will be able to use the third dimension for their mobility needs. The traditional aviation industry and high-tech newcomers alike are making huge investments to make this - still unproven - technology a reality. Although Unmanned Aerial Systems (UAS) have now for some time been used in segregated airspace where separation from other air traffic can be assured, potential users have interests to deploy UAS in non-segregated airspaces. Recent technological and operational improvements give reason to believe that UAS safety and performance capabilities are maturing. However, there is still the need for establishing a systematic agreement between UAS safety policies with commonly accepted UAS Safety Risk Management processes. This agreement is needed to show that the risks related to UAS operations in all the different airspace classes can be adequately controlled in a way that would not jeopardize current safety levels and safety mitigations effectiveness. This study aims to investigate the current status of UAS operations and future concepts of operations with specific interest in the management of safety risk. This manuscript aims to summarize some of regulatory aspects currently available linked to safety investigation and reporting of drone operations and consequently draw some potential lines for future research.

Wind Shear of Low-Level Jets and Their Influence on Manned and Unmanned Fixed-Wing Aircraft during Landing Approach

Wind shear at low altitudes represents a potential hazard to landing aircraft. Based on two wind lidar data sets of one year, the occurrence of low-level jets (LLJs), the vertical wind shear and the rotation of the wind direction were analysed. The lidar system was located at the sites of Braunschweig in the North German Plain, Germany, and Clausthal-Zellerfeld in the low mountain range Harz, Germany. The observed wind shear gradients between the altitude of 40 m and the altitude of the maximum wind speed was in the range of −0.23 s−1 to +0.20 s−1. The rotation of the wind direction with altitude occurred both in clockwise and anticlockwise direction. The ratio of clockwise versus anticlockwise occurrence of directional shear was 4:1 for Braunschweig and 3:1 for Clausthal-Zellerfeld. The observed wind shear gradients were compared to values for hazard potential of different levels for a typical aircraft. Although the LLJ was not hazardous for manned aircraft in any observed case, the awareness of LLJ helps to reduce the pilot’s workload and possible pilot-introduced oscillations caused as a result of the wind shear and aircraft characteristics. In contrast to manned aviation, the value of changes in wind speed and direction during LLJ conditions can cause significant risks for unmanned aerial system operations with less than 25 kg of take-off weight. This is a result of the lower airspeed-wind-speed ratio and the flight control and flight planning.

НАВЧАЛЬНО-ТРЕНУВАЛЬНА СИСТЕМА ДЛЯ ПІДГОТОВКИ ОПЕРАТОРІВ БЕЗПІЛОТНИХ АВІАЦІЙНИХ КОМПЛЕКСІВ

In order to meet the needs of the Armed Forces of Ukraine (AFU) for specialists in the operation of unmanned aerial systems, the Zhitomir Military Institute named by S. P. Korolev deployed training for operators - military pilots. While creating the material and technical base, the issue of developing and introducing into the training process of simulators that would meet the requirements of higher military education training. Development of the scientific training system was carried out on the basis of the list of basic training issues, profound mastery of which is mandatory for the UAV operator’s. The training system was developed, manufactured and implemented in the training process, which is built as a schematic-abstracted one to ensure the conditions of effective learning material assimilation. The content basis of the scientific training system is a flat schematic outline of the aircraft, which contains typical onboard equipment of unmanned aerial vehicles and a reconstructed connection scheme of the elements. The power of the onboard equipment is provided from the classroom power supply via a stabilized power supply unit. Operation of the onboard equipment can be controlled from the manual control panel and from the ground control station via the Mission Planner program. The Mission Planner can also be controlled from the X - Plane flight simulator. In flight simulation mode, the Mission Planner screen displays a map of the flight route, the X-Plane screen displays the view and spatial orientation as well as the corresponding servo drives of the aircraft's steering surfaces and the main engine operation modes. The software of the scientific training system allows planning and adjusting the route and flight program, practicing UAV piloting skills in the flight simulator mode, simulating flight in different weather conditions. The scientific training system includes a two-channel hardware-software oscilloscope which allows to research electric processes in different electric lines of airborne equipment of the aircraft and pair interconnections between them. Functional properties of scientific training system allow to study theoretically and practice practically a wide range of training issues required in training of UAV operators. Up to this circle includes both the issues necessary for mastering drone piloting and the issues necessary for mastering the maintenance and repairs of UAV.

Assessment of the Emerging Landscape of Unmanned Aerial Systems in Trinidad and Tobago

Interest in the civilian applications of Unmanned Aerial Systems (UAS) has been growing worldwide, especially in government and commercial tasks such as surveillance, search and rescue, inspection of infrastructure, agriculture, mining, and mapping. Likewise, Trinidad and Tobago (T&amp;T) has been witnessing a growing interest and application of commercial and non-commercial UAS operations. However, there is little assessment for the growth of the UAS market nor is there characterisation of UAS-based activities since the pertinent regulations established in 2016. This study seeks to formally identify the emerging UAS landscape in T&amp;T during the period 2015 to 2019. As such, this study maps and characterises the spatial and temporal patterns of UAS distribution, then appraises the various categories for the existing operations. To achieve these goals, this study utilised qualitative and quantitative techniques of Geoinformatics. The intent for this study is to provide a perspective on the growth and the implications of the UAS industry in T&amp;T, and to guide strategic planning among organisations with a stake in the emergence of UAS into civil airspace.

Application of Dempster–Shafer Networks to a Real-Time Unmanned Systems Risk Analysis Framework

Unmanned aerial systems (UASs) are continuing to proliferate. Quantitative risk assessment for UAS operations, both a priori and during the operation, are necessary for governing authorities and insurance companies to understand the risks and properly approve operations and assign insurance premiums, respectively. In this paper, the problem of UAS risk analysis and decision making is treated through a novel application of Dempster–Shafer (DS) networks using auto-updating transition matrices. This method was motivated by the results of the 2018 UAS Safety Symposium held at the Georgia Institute of Technology, which was conducted as part of the research detailed in this paper. The paper describes training a DS network based on simulated operation data, testing the capabilities of the trained network to make real-time decisions on a small UAS against a baseline system in a representative mission, and exploring how this system would extend to a more inclusive UAS ecosystem. Conclusions are drawn with respect to the research performed, and additional research directions are proposed.

Extracting the topology of urban airspace through graph abstraction

With the rapid adoption of the operational concept of Unmanned Aerial Systems (UAS) in urban airspace, there is an increased focus on the spatial extent that Unmanned Aircraft (UA) can safely navigate. Urban airspace is full of intrinsic risks associated with several factors, including but not limited to unpredictable microclimates, radio-frequency disturbances and electro-magnetic interferences. For safe and efficient use of airspace, it is imperative to proactively assess the availability of airspace volumes to accommodate large-scale operations. In this paper, we highlight that urban airspace is a unique environment where highly obstructed (complex topology) and sparsely structured (simple topology) regions coexist. The presence of static obstacles and required separation from those obstacles create particular spatial structures, such as narrow passages, islands and funnels, throughout the airspace. Considering that not only throughput capacity of airspace but also complexity of path planning is highly dependent on the topology of a navigable space, we propose a new airspace assessment approach to extract the topology of airspace using computational geometry techniques. We focus on identifying geospatial locations suitable for high density UAS operations as well as examining spatial contiguity between those locations in highly urbanized areas. In doing so, we define segment as an airspace region that is wide enough for multiple vehicles to simultaneously pass through. Low-altitude urban airspace is abstracted into a compact and informative graph structure called segment graph that summarizes segment connectivity in the horizontal and vertical dimension. The proposed method shows that the geometry of low-altitude airspace is fundamentally different from that of conventional high-altitude airspace and can provide a useful basis for airspace design and management within low-altitude urban environments.

Prognostics for Autonomous Electric-Propulsion Aircraft

An autonomous unmanned aerial system (UAS) needs, during the flight, accurate information about the current failure state of the aircraft and its capabilities in order to safely perform its mission and properly react to contingencies. The flight battery of an electric-propulsion aircraft is its most relevant resource. Model-based prognostics algorithms are used to obtain good estimates of its current state of charge and remaining capacity. However, these algorithms can have a large computational footprint. We present Prognostics-as-a-Service, a hybrid approach combining on-board computation with server-based prognostics on the ground.In this paper, we focus on the role, battery prognostics plays for the safe operation of a highly autonomous aircraft: prognostics for (1) continuous on-board safety monitoring, (2) for UAS operations, and (3) for contingency planning. We present the NASA Autonomous Operating System (AOS) and discuss how the autonomous components closely work together with on-board and server-based ground prognostics systems. We will illustrate the system with case studies on small NASA unmanned aircraft.

Identification of Wind-Induced Hazard Zones Impacting UAS Bridge Inspection

Unmanned Aerial Systems (UAS) continue to grow in both popularity and utility within the national airspace system. The use of commercial UAS for civil inspection, specifically that of bridge structures, is becoming commonplace among practitioners and academics alike. The development of an integrated bridge-inspection hazard model provides a way for UAS operators to prepare for and respond to changing environmental conditions that could otherwise prevent a successful UAS flight. The interaction of wind-induced airflow with bridge surfaces creates an aerodynamic wake that can result in hazardous conditions for a UAS platform operating in close proximity. An analysis of this airflow surrounding an overpass bridge using computational fluid dynamic (CFD) models shows where these hazardous areas exist, based on initial wind conditions, existing functionality of UAS platforms, and mitigating systems that exist within current UAS technology. Altering the initial conditions by modifying wind velocities allows for a baseline understanding of which areas surrounding an overpass bridge structure are not suitable for successful UAS flight. Hazard zones range from severe, moderate, and mild, to no appreciable hazard. Moderate to extreme hazard zones are located in areas where high levels of wind shear, vorticity, or general turbulence exist, making UAS operations difficult. This study develops a practical model that may be utilized by UAS operators to better understand and potentially avoid unsafe flight environments during bridge structure inspections.

Method to Characterize Potential UAS Encounters Using Open Source Data

As unmanned aerial systems (UASs) increasingly integrate into the US national airspace system, there is an increasing need to characterize how commercial and recreational UASs may encounter each other. To inform the development and evaluation of safety critical technologies, we demonstrate a methodology to analytically calculate all potential relative geometries between different UAS operations performing inspection missions. This method is based on a previously demonstrated technique that leverages open source geospatial information to generate representative unmanned aircraft trajectories. Using open source data and parallel processing techniques, we performed trillions of calculations to estimate the relative horizontal distance between geospatial points across sixteen locations.