Small Drones Research Articles

Casualty Risk Analysis for Remotely Piloted Aircraft Systems Operations

This paper offers an alternative Casualty Area assessment. This parameter appears in all flying vehicles risk evaluation. This work arises from the intention of contributing to the subject of risk assessment in aviation. All the formulations of the Casualty Area — which will be analyzed in this paper — are tailored for debris with high kinetic energies. These models lead to an overestimation of the risk associated with small drones flight, preventing both their use and the implied operational benefits. The proposed version tailors the small Remotely Piloted Aircraft Systems (commonly known as drones) falling under the A2 European Aviation Safety Agency (EASA) category, C2 class [European Aviation Safety Agency, Civil drones (Unmanned aircraft, 2018), https://www.easa.europa.eu/easa-and-you/civil-drones-rpas , accessed November (2019)], i.e. drones with a mass up to 4 kg. To obtain the new formulation, the authors started with the most used formula, proposed by Montgomery [R. M. Montgomery and J. A. Ward, Casualty Areas from Impacting Inert Debris for People in the Open (Research Triangle Institute, 1995)], used by FAA (Federal Aviation Administration, [Range Safety Group, Common Risk Criteria for National Test Ranges Inert Debris (Range Commanders Council, 2000)] and [Range Safety Group, Common Risk Criteria Standards for National Test Ranges (Range Commanders Council, 2010)]), adopting new hypotheses but following the same process. The results allow a risk formulation more suitable for drones of the above-mentioned size [Range Safety Group, Range Safety Criteria For Unmanned Air Vehicles Supplement (Range Commanders Council, 1999)]. The proposed formulation can be of use for specific regulatory issues. As a matter of fact, many services use small drones: aerial photography during public assemblies, concerts, sporting events, home deliveries, buildings thermal evaluation, to name just a few. The implementation of the present results allows a wider series of operations previously restricted due to the estimation of an incompatible level of risk. In fact, with the new formulation of the Casualty Area, the level of risk is safely lowered, mainly addressing the small dimension drones [European Aviation Safety Agency, Civil drones (Unmanned aircraft), https://www.easa.europa.eu/easa-and-you/civil-drones-rpas , Online accessed November (2019)]. The steps leading to the final formulation derive from a comprehensive analysis, coherent with the guidelines set by FAA and EASA.

The Use of Ethanol as an Alternative Fuel for Small Turbojet Engines

The use of alternative fuels to traditional kerosene-based ones in turbo-jet engines is currently being widely explored and researched. However, the application of alternative fuels in the area of small turbojet engines with thrust ratings up to 2 kilo-newtons, which are used as auxiliary power units or to propel small aircraft or drones, is not as well researched. This paper explores the use of ethanol as a sustainable fuel and its effects on the operation of a small turbojet engine under laboratory conditions. Several concentrations of ethanol and JET A-1 mixtures are explored to study the effects of this fuel on the basic parameters of a small turbojet engine. The influence of the different concentrations of the mixture on the start-up process, speed of the engine, exhaust gas temperature, and compressor pressure are evaluated. The measurements shown in the article represent a pilot study, the results of which show that ethanol can be reliably used as an alternative fuel only when its concentration in a mixture with traditional fuel is lower than 40%, yielding positive effects on the operating temperatures and small negative effects on the speed or thrust of the engine.

Safety Enhancement of UAVs from the Signal Processing’s Perspectives: A Bird’s Eye View

Unmanned air vehicles (UAVs) or drones have gained popularity in recent years. However, the US Federal Aviation Administration (FAA) is still hesitant to open up the national air space (NAS) to UAVs due to safety concerns because UAVs have several orders of magnitude of more accidents than manned aircraft. To limit the scope in this paper, we focus on large, heavy, and expensive UAVs that can be used for cargo transfer and search and rescue operations, not small radio-controlled toy drones. We first present a general architecture for enhancing the safety of UAVs. We then illustrate how signal processing technologies can help enhance the safety of UAVs. In particular, we provide a bird’s eye view of the application of signal processing algorithms on condition-based maintenance, structural health monitoring, fault diagnostics, and fault mitigation, which all play critical roles in UAV safety. Some practical applications are used to illustrate the importance of the various algorithms.

The UJI Aerial Librarian Robot: A Quadcopter for Visual Library Inventory and Book Localisation.

Over time, the field of robotics has provided solutions to automate routine tasks in different scenarios. In particular, libraries are awakening great interest in automated tasks since they are semi-structured environments where machines coexist with humans and several repetitive operations could be automatically performed. In addition, multirotor aerial vehicles have become very popular in many applications over the past decade, however autonomous flight in confined spaces still presents a number of challenges and the use of small drones has not been reported as an automated inventory device within libraries. This paper presents the UJI aerial librarian robot that leverages computer vision techniques to autonomously self-localize and navigate in a library for automated inventory and book localization. A control strategy to navigate along the library bookcases is presented by using visual markers for self-localization during a visual inspection of bookshelves. An image-based book recognition technique is described that combines computer vision techniques to detect the tags on the book spines, followed by an optical character recognizer (OCR) to convert the book code on the tags into text. These data can be used for library inventory. Misplaced books can be automatically detected, and a particular book can be located within the library. Our quadrotor robot was tested in a real library with promising results. The problems encountered and limitation of the system are discussed, along with its relation to similar applications, such as automated inventory in warehouses.

An Efficient and Secure Certificate-Based Access Control and Key Agreement Scheme for Flying Ad-Hoc Networks

The evolution of Flying Ad-hoc Networks (FANETs) marks the paradigm shift from a single large drone to multiple small drones linked together in an ad-hoc fashion. To maintain the Quality of Service (QoS) in the multi-hop networking schema, FANETs utilize the available resources efficiently. However, due to open wireless boundary and high mobility of the drones, the FANETs are vulnerable to malicious nodes that can penetrate the network and, thus, pose serious security threats, particularly at the Medium Access Control (MAC) layer. Such susceptibility compromises the network security and privacy and harms the information exchange operation within the network. The attacker can either transmit a large number of reservation requests to waste the bandwidth, listen to the control messages, conduct power-efficient jamming or falsify the information to manipulate the network control. Therefore, secure access control and a key agreement mechanism are required. The mechanism must utilize the two phases, i.e., node authentication and key agreement, to counter the aforementioned attacks. Our contribution, in this paper, is a certificate-based access control and key agreement scheme, which is based on the technique of Hyperelliptic Curve Cryptography (HECC) and employs a collision-resistant one-way cryptographic hash function. In order to assess the viability and performance of the proposed scheme, we analyze it using formal security analysis techniques, such as the Real-Or-Random (ROR) model and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. The scheme is also evaluated using the informal security analysis technique, or the non-mathematical approach. The results obtained from both analyses affirm the superiority of our proposed scheme.

Study on Extraction of Landslide Information Based on UAV Survey

Traditional analysis of landslide evolution discipline requires particular on-site investigation, which not only consumes a lot of manpower and material resources, but is also very inefficient. With the development of small drone aerial photography technology, a method based on the whole area landslide measurement becomes possible. This paper uses the rapid development of digital photogrammetry technology in recent years to monitor the surface deformation of the Qinyu landslide, and conducts an in-depth study of its evolution. The results show that the evolution of the Qinyu landslide is inherited and different in time and space. The reconstruction of the three-dimensional model greatly simplifies the traditional on-site investigation, and it also provides new methods and ideas for landslide monitoring.

Advanced Stationary Point Concentration Technique for Leakage Mitigation and Small Drone Detection With FMCW Radar

With the increase in threats posed by small drones, the development of radars to detect such drones has become a key necessity. In earlier studies, we proposed the stationary point concentration (SPC) technique for small drone detection using frequency-modulated continuous-wave (FMCW) radar. The SPC technique is a novel approach for mitigating leakage, which is an inherent problem in FMCW radar. The SPC technique improves the signal-to-noise ratio of small drones by reducing the noise floor and provides accurate distance and velocity information of such drones. However, this technique has shortcomings in its realization. In this article, we present the drawbacks of this technique and propose an advanced SPC (A-SPC) technique. The proposed technique can overcome the drawbacks of the SPC technique while implementing the benefits of the SPC technique. The experimental results verify the proposed A-SPC technique and demonstrate its robustness and usefulness.

Antidrone Wireless Personal Shield

The evolution of small drone technology raises new challenges regarding personal privacy due to the acquisition and flight of unlicensed small drones. Many of these small drones are controlled over Wi-Fi connection making them inexpensive and easy to control. Latest discoveries in vulnerabilities of wireless network protocols give us the advantage to use cyber-attacks as a method of defense. This paper is addressing general audience on how to create a personal shield against small drones with the advantage of being nonintrusive to the other surrounding wireless networks and, at the same time, protecting your personal privacy of a rogue drone.

A Ka-Band MMIC LNA in GaN-on-Si 100-nm Technology for High Dynamic Range Radar Receivers

A Ka-band monolithic low-noise amplifier (LNA) with high gain and high dynamic range (DR) has been designed and implemented in a 100-nm gallium nitride (GaN)-on-Si technology. The LNA is designed as the first stage of a high DR receiver in an frequency modulated continuous wave (FMCW) radar for the detection of small drones. The three-stage monolithic microwave integrated circuit (MMIC) LNA has a linear gain of 26 dB and a noise figure (NF) of 2 dB in the frequency band 33-38 GHz. The output 1-dB compression point (P1dB) and output IP3 at 37 GHz are 20 and 28.4 dBm, respectively. To our knowledge, this combination of NF, gain, and DR performance represents the state of art in this frequency band.

Visualizations of the small military drone: normalization through ‘naturalization’

ABSTRACT We are in the midst of a global turn to the drone. Responding to the ‘unmanning’ of contemporary warfare, interdisciplinary scholarship has interrogated the human operators and non-human actors underpinning the drone, and their wide-ranging ethical, geopolitical, and legal implications. A key facet of extant drone debates surrounds drone vision – both as it operationally visualizes and is fetishized. While comparatively nascent, scholars have begun to explore how drones are instead visualized across particular media. In this article I identify two lacuna within extant drone scholarship: first a lack of attentiveness to small military drones, which while comprising the majority of global military arsenals remain comparatively absent from scholarly analysis; and second, a need to attend to a greater diversity of visual representations of the drone. In response, this article explores promotional visualizations of small military drones as they are ethnographically-encountered at a key site through which their usage is compelled and their functioning enabled – the defence tradeshow. In so doing, I identify three central frames through which the drone is repeatedly represented therein. I argue that these frames both engage and employ visual conventions associated with ‘nature’ and the ‘natural’ in order to ‘naturalize’ and normalize the drone in as-yet unaccounted ways. Approaching the drone through the current, yet under-examined, visual milieu of the defence environments in which it is promoted, the article contributes to both interdisciplinary drone scholarship, and literatures exploring the visual cultures of militarism more widely.

Drone Security: Issues and Challenges

Recent advancements in drone technology are opening new opportunities and applications in various fields of life especially in the form of small drones. However, these advancements are also causing new challenges in terms of security, adaptability, and consistency. This research discusses the drone technology, area of usages, citizen multi-objective uses, drones security, protection, and secrecy apprehensions, drone current intimidations and susceptibilities, existing approaches for drone cyber-security methods, security threats to drones and data sources for current literature review. Small drones are proving to be a new opportunity for the civil and military industries. The small drones are suffering from architectural issues and the definition of security and safety issues. The rapid growth of the Internet of Things (IoT) opens new dimensions for drone technology but posing new threats as well. The tiny flying intelligent devices are challenging for the security and privacy of data. The design of these small drones is yet not matured to fulfill the domain requirements. The basic design issues also need security mechanisms, privacy mechanisms and data transformations.

IoT-based Cyber-security of Drones using the Naïve Bayes Algorithm

Recent advancements in drone technology are opening new opportunities and applications: in various fields of life especially in the form of small drones. However, these advancements are also causing new challenges in terms of security, adaptability, and consistency. Small drones are proving to be a new opportunity for the civil and military industries. The small drones are suffering from architectural issues and the definition of security and safety issues. The rapid growth of the Internet of things opens new dimensions for drone technology but posing new threats as well. The tiny flying intelligent devices are challenging for the security and privacy of data. The design of these small drones is yet not matured to fulfill the domain requirements. The basic design issues also need security mechanisms, privacy mechanisms, and data transformations. The aspects like intrusion and interception in the domain of the Internet of Drones (IoD) need to be investigated to make these timely drones more secure and more adaptable. In this paper, we have used intelligent machine learning approach to design an IoT aided drone. This approach will provide intelligent cyber security system which will help in detecting network security threats using Blockchain.

Fast Depth Prediction and Obstacle Avoidance on a Monocular Drone Using Probabilistic Convolutional Neural Network

Recent studies employ advanced deep convolutional neural networks (CNNs) for monocular depth perception, which can hardly run efficiently on small drones that rely on low/middle-grade GPU(e.g. TX2 and 1050Ti) for computation. In addition, the methods which can effectively and efficiently produce probabilistic depth prediction with a measure of model confidence have not been well studied. The lack of such a method could yield erroneous, sometimes fatal, decisions in drone applications (e.g. selecting a waypoint in a region with a large depth yet a low estimation confidence). This paper presents a real-time onboard approach for monocular depth prediction and obstacle avoidance with a lightweight probabilistic CNN (pCNN), which will be ideal for use in a lightweight energy-efficient drone. For each video frame, our pCNN can efficiently predict its depth map and the corresponding confidence. The accuracy of our lightweight pCNN is greatly boosted by integrating sparse depth estimation from a visual odometry into the network for guiding dense depth and confidence inference. The estimated depth map is transformed into Ego Dynamic Space (EDS) by embedding both dynamic motion constraints of a drone and the confidence values into the spatial depth map. Traversable waypoints are automatically computed in EDS based on which appropriate control inputs for the drone are produced. Extensive experimental results on public datasets demonstrate that our depth prediction method runs at 12Hz and 45Hz on TX2 and 1050Ti GPU respectively, which is 1.8X~5.6X faster than the state-of-the-art methods and achieves better depth estimation accuracy. We also conducted experiments of obstacle avoidance in both simulated and real environments to demonstrate the superiority of our method to the baseline methods.

Securing Internet of Drones With Identity-Based Proxy Signcryption

Internet of Drones (IoD) is a decentralized networking architecture that makes use of the internet for uniting drones to enter controlled airspace in a coordinated manner. On the one hand, this new clan of interconnected drones has ushered in a new era of real-world applications; Small drones, on the other hand, are generally not designed with security in mind, making them exposed to fundamental security and privacy concerns. Limited computing capabilities, along with communication over an open wireless channel, exacerbate these challenges, making the IoD unfeasible for secure operations. In this article, we propose an identity-based proxy signcryption scheme to address these issues. During data transfer between drones and to the cloud server, the proposed scheme supports outsourcing decryption and member revocation. The proposed scheme is based on the notion of Hyper Elliptic Curve Cryptography (HECC), which improves network computation efficiency. We use formal security analysis with the Random Oracle Model (ROM) to evaluate security toughness. The performance analysis of the proposed scheme has also been reviewed in terms of computation and communication costs with the relevant existing schemes. The results obtained from both the security and performance analyses affirm the superiority of the proposed scheme.

Behavioural and physiological responses of captive Antillean manatees to small aerial drones

Abstract Context Unmanned aerial vehicles or drones are powerful tools for wildlife research. Identifying the impacts of these systems on target species during operations is essential to reduce risks of disturbance to wildlife, to minimise bias in behavioural data, and to establish better practices for their use. Aims We evaluated the responses of captive Antillean manatees to the overhead flight of a small aerial drone. Methods We used aerial and ground videos to compare manatee activity budgets and respiration rates in three 15-min sampling periods: ‘before’, ‘during’ and ‘after’ flights with a DJI Phantom 3 Advanced. The drone was hovered stationary for 3 min at five altitudes (100 m, 40 m, 20 m, 10 m, 5 m) to determine whether manatees display behavioural responses compared with the control period, and whether they respond more at lower altitudes. Only one flight was performed per manatee group to avoid bias owing to habituation to the drone. Key results Manatees responded to drone flights by (1) increasing their activity levels during and after flights, therefore signalling after effects; (2) decreasing their respiration rate during flights; and (3) displaying behavioural reactions including grouping, tail-kicking, fleeing from their original position and moving under submerged structures. From the 11 individuals displaying behavioral reactions, 9 reacted in the first ~2 min of flight, preventing assessments of altitude effects and suggesting manatees responded to the drone sound at take-off. Conclusions Behavioural changes of responding manatees were similar to previous reports of disturbance responses to boats and drones in this species. Our use of a control period showed shifts in respiration rates and activity budgets that persisted after flights. Several manatees reacted to the drone from the time of take-off and first minutes of flight, indicating that the sound of the electric rotors could be a strong negative stimulus to manatee and highlighting the importance of establishing safe distances for take-off. Implications Future studies should consider that drones could elicit conspicuous and inconspicuous responses in manatees. Our results emphasise the need for control data on animal behaviour to better assess the impact of drones on wildlife and to design non-invasive protocols.

Small UAS and Delivery Drones: Challenges and Opportunities The 38th Alexander A. Nikolsky Honorary Lecture

During the past two decades, there has been major growth of small-unmanned aerial vehicles (sUAV) for hobbyists and rapidly expanding commercial and military applications. The impetus for this dramatic expansion has been due to the explosion of mobile technology in terms of microelectronics, data processing and transmission capability, high-energy-density batteries, miniaturized integrated programmable chips, and innovations in computer vision and videography/photography. However, there are many challenges to overcome before these small unmanned aerial systems (sUAS) can be used for routine commercial and military applications, which include reliability, sizable payload and range, stringent navigation/guidance requirements, and precision takeoff/landing and robust autonomous flight in constrained and low-altitude gusty environment. The objective of this paper is to cover state-of-the-art of sUAS and delivery drones, identify technology gaps and key scientific barriers, and present future research needs for high payoff applications.

Беспилотная техника для целей лесного комплекса и мониторинга состояния водных объектов

Military-industrial complexes of many countries have invested billions of dollars in the industry over 120 years of development and have achieved significant progresses in the creation of surface, water and underwater equipment. Groups of military unmanned vehicles include unmanned aerial vehicles (UAVs), deck-based UAVs, water, underwater and hybrid unmanned vehicles (UAVs). Their purpose is intelligence, surveillance, strategic research projects, and military transport purposes. As for the civilian use of unmanned vehicles, this is a young industry, it is 15 years old. The beginning of the era of non-military unmanned aerial vehicles (UAVs) and then unmanned floating vehicles (UAVs) is considered to be 2006, when the US Federal Aviation Administration allowed the flights of small custom drones. At the same time, they were given a definition: a device that is remotely controlled by an operator; a device that moves along a pre-planned route. Unmanned vehicles the use of which for the purposes of the forest complex of our country is carried out or is planned to begin in the near future must meet some special requirements that are discussed in this article.

An Energy-Aware and Predictive Fuzzy Logic-Based Routing Scheme in Flying Ad Hoc Networks (FANETs)

Today, unmanned aerial vehicles (UAVs), also known as drones, have become very popular in military applications, commercial applications, and academic research. Flying ad hoc network (FANET) is a new type of ad hoc network, which groups small drones into an ad hoc form. These networks have unique characteristics, including moving in a 3D space, high mobility, frequent topological changes, limited resources, low density of nodes, and so on, which impose various challenges when designing a proper and efficient routing scheme. In this paper, we present a fuzzy logic-based routing scheme for flying ad hoc networks. The proposed routing scheme has two phases: route discovery phase and route maintenance phase. In the first phase, we propose a technique for calculating the score of each node in the network to prevent the broadcast storm problem and control the flood of the control messages, which have been broadcast to discover a new route in the network. This score is calculated based on various parameters such as movement direction, residual energy of nodes, link quality, and node stability. Moreover, in the route selection process, we design a fuzzy system to select routes with more fitness, less delay, and fewer hops for data transfer. The second phase includes two steps: preventing route failure in order to detect and modify paths at the failure threshold, and reconstructing failed routes in order to recognize and quickly replace these routes. Finally, the proposed routing scheme is implemented in NS2 to evaluate its performance and determine its efficiency. The simulation results are compared with three routing methods, namely ECaD, LEPR, and AODV. These results show that the proposed routing method outperforms other routing schemes in terms of end to end delay, packet delivery rate, route stability, and energy consumption. However, it has slightly increased the routing overhead.

Examination of risk management perspectives in pilot training of small drone

Examination of risk management perspectives in pilot training of small drone

Target Detection Through Riemannian Geometric Approach With Application to Drone Detection

Radar detection of small drones in presence of noise and clutter is considered from a differential geometry viewpoint. The drone detection problem is challenging due to low radar cross section (RCS) of drones, especially in cluttered environments and when drones fly low and slow in urban areas. This paper proposes two detection techniques, the Riemannian-Brauer matrix (RBM) and the angle-based hybrid-Brauer (ABHB), to improve the probability of drone detection under small sample size and low signal-to-clutter ratio (SCR). These techniques are based on the regularized Burg algorithm (RBA), the Brauer disc (BD) theorem, and the Riemannian mean and distance. Both techniques exploit the RBA to obtain a Toeplitz Hermitian positive definite (THPD) covariance matrix from each snapshot and apply the BD theorem to cluster the clutter-plus-noise THPD covariance matrices. The proposed Riemannian-Brauer matrix technique is based on the Riemannian distance between the Riemannian mean of clutter-plus-noise cluster and potential targets. The proposed angle-based hybrid-Brauer technique uses the Euclidean tangent space and the Riemannian geodesical distances between the Riemannian mean, the Riemannian median and the potential target point. The angle at the potential target on the manifold is computed using the law of cosines on the manifold. The proposed detection techniques show advantage over the fast Fourier transform, the Riemannian distance-based matrix and the Kullback-Leibler (KLB) divergence detectors. The validity of both proposed techniques are demonstrated with real data.