• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.103-111
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• 2021

The purpose of this study is to study a method for preventing collisions of multiple drones in controlled airspace. As a result of the study, it was proved that it is appropriate as a method to control drone collisions after setting accurate information on the ROI (Region of Interest) area estimated based on the expected drone path and time in the control system as a method to avoid drone collision. As a result of the empirical analysis, the diameter of the flight path of the operating drone should be selected to reduce the risk of collision, and the change in the departure time and operating speed of the operating drone did not act as an influencing factor in the collision. In addition, it has been demonstrated that providing flight priority is one of the appropriate methods as a countermeasure to avoid collisions. For collision avoidance methods, not only drone sensor-based collision avoidance, but also collision avoidance can be doubled by monitoring and predicting collisions in the control system and performing real-time control. This study is meaningful in that it provided an idea for a method for preventing collisions of multiple drones in controlled airspace and conducted practical tests. This helps to solve the problem of collisions that occur when multiple drones of different types are operating based on the control system. This study will contribute to the development of related industries by preventing accidents caused by drone collisions and providing a safe drone operation environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.943-948
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• 2022

Drones have been widely used in various fields due to the rapid development of done-related technologies, which causes various problems. The schemes which can track target drones by using signal transmitted by target drones have been investigated as a key technology for anti-drone systems to solve these problems. In this paper, we investigate an illegal drone tracking system based on swarming flight that consists of multiple small drones in order to resolve the limitations of a conventional system that consists of a single drone. In addition, we also propose a scheme with which we can adaptively adjust the separation distance between small drones in a swarm according to channel situations. We analyzed the performance of the proposed scheme in terms of success ratio and the number of movements. The proposed scheme can improve the success ratio and the number of movements by 170% and 63% respectively, compared to the conventional scheme.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.247-257
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• 2020

The Purpose of this study is to present effective Anti-Drone systems to protect national important facilities against drones that are illegally used by crime groups and terrorists with malicious intents. In order to accomplish the purpose of the study, technical and policy reports regarding Anti-Drone systems, open documents from manufacturers and various research papers are reviewed, and in-depth interviews with experts were conducted. Studies have shown that it is effective to overlay and mix different detection systems so that they can improve detection rates by supplementing each other's advantages and disadvantages, and that the means of incapacitation need to acquire flexibility by using both soft-kill and hard-kill methods in accordance with operational environment for the effective usage. In other words, the establishment of an illegal drone pre-management system, mixed and overlapping detection assets, determining appropriate countermeasures, and multiple distribution of means of incapacitation. The establishment of a protection system for important national facilities through the operation of overlapping and complex anti-drone systems is the most urgent task.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.47-54
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• 2019

Social dredging of various river facilities, such as dams and agricultural reservoirs currently being constructed, should be done to ensure stable reservoirs. However, it is difficult to find a system that tells the exact amount of water in real-time in a reservoir or dam. These measurements require an automated system to collect and analyze highly accurate data in real time. In this study, we propose a method to measure the amount of water and soil of reservoir in real time through multi-division volume calculation using a drone, and this method can detect sediment conditions in real time and determine the exact timing and scale of dredging.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.07a
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• pp.308-309
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• 2015

최근 들어 일반인들도 다중 콥터와 4k 고성능 카메라를 장착한 상용 드론을 구매하여 자신의 취미 활동용으로 사용하고 있다. 드론을 이용한 많은 동호회가 생겨나고 1인 1드론, 개인용 드론의 시대가 시작되고 있다. 또한 사물인터넷의 시대에 걸맞게 아두이노, 라즈베리파이와 같은 오픈하드웨어 플랫폼과 오픈 소스를 이용하고 저가형 3D printer 의 보급으로 자신만의 독특한 형태를 지니는 기체 제작을 시작하고 있다. 이에 본 논문에서는 3D 캐드를 이용한 위상최적화 기법을 적용하여 기존 상용 기체의 강성은 그대로 유지하되 기체 프레임 무게를 절반으로 줄인다. 또한, 풍동실험을 진행해서 기존 기체에서 발생하는 유체흐름을 분석하고 새로운 기체를 적용했을 경우에도 유사한 유체흐름이 나타나도록 설계하여 3D 프린터를 사용하여 제작하였다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.5
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• pp.437-446
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• 2017

An integrated flight simulation program for multicopter drones is presented. The program includes rigid body dynamics, propeller thrust, battery energy, control, and air. Using this program, users can monitor and analyze the states of drones along flight trajectories. As a programming language, Modelica has been chosen, that specializes in simulation program development. Modelica enables users to develop simulation programs efficiently due to acausal and object oriented properties. For missions including horizontal and vertical maneuvers, many dynamical states of drones have been analyzed with simulation results.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.437-447
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• 2020

The purpose of this study is to research the countermeasures and expected effects through the use of drones in the field of disaster prevention as a drone-based smart quarantine performance method. The environmental, market, and technological approaches to the review of the current quarantine performance task and its countermeasures are as follows. First, in terms of the environment, the effectiveness of the quarantine performance business using drone-based control is to broaden the utilization of forest, bird flu, livestock, facility areas, mosquito larvae, pests, and to simplify and provide various effective prevention systems such as AI and cholera. Second, in terms of market, the standardization of livestock and livestock quarantine laws and regulations according to the use of disinfection and quarantine missions using domestic standardized drones through the introduction of new technologies in the quarantine method, shared growth of related industries and discovery of new markets, and animal disease prevention It brings about the effect of annual budget savings. Third, the technical aspects are (1) on-site application of disinfection and prevention using multi-drone, a new form of animal disease prevention, (2) innovation in the drone industry software field, and (3) diversification of the industry with an integrated drone control / control system applicable to various markets. (4) Big data drone moving path 3D spatial information analysis precise drone traffic information ensures high flight safety, (5) Multiple drones can simultaneously auto-operate and fly, enabling low-cost, high-efficiency system deployment, (6) High precision that this was considered due to the increase in drone users by sector due to the necessity of airplane technology. This study was prepared based on literature surveys and expert opinions, and the future research field needs to prove its effectiveness based on empirical data on drone-based services. The expected effect of this study is to contribute to the active use of drones for disaster prevention work and to establish policies related to them.

• Journal of Advanced Navigation Technology
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• v.25 no.4
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• pp.273-279
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• 2021

A flight control computer(FLCC) applied to an unmanned aerial vehicle(UAV) is a safety-critical item, and which is designed in a multiple structure to increase the reliability of operation by securing fault tolerance. These FLCC of multiple structure should be designed so that each independent processing/control components can perform the same operation at the same time. And for this reason, a synchronization algorithm for synchronizing the operation between FLCCs should be included in an operational flight program. In this paper, we propose a software design method for synchronization between dual FLCCs applied to UAVs. The proposed synchronization method is designed to synchronize using only the minimum hardware resources to reduce a failure rate. In addition, the proposed synchronization method is designed to minimized synchronization errors due to a timer operation by designing in consideration of operation characteristics of the hardware timer used for the synchronization.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.83-99
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• 2021

With the advent of the fourth industrial revolution, studies on driving management and driving strategies of autonomous vehicles are emerging. While obtaining microscopic traffic data on vehicles is essential for such research, we also see that conventional traffic data collection methods cannot collect the driving behavior of individual vehicles. In this study, UAV videos were used to collect traffic data from the viewpoint of the aerial base that is microscopic. To overcome the limitations of the related research in the literature, the micro-traffic data were estimated using the multiple object tracking of deep learning and an image registration technique. As a result, the speed obtained error rates of MAE 3.49 km/h, RMSE 4.43 km/h, and MAPE 5.18 km/h, and the traffic obtained a precision of 98.07% and a recall of 97.86%.

• Electronics and Telecommunications Trends
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• v.35 no.4
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• pp.81-90
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• 2020

The use of machine learning technologies such as deep and reinforcement learning has proliferated in various domains with the advancement of deep neural network studies. To make the learning successful, both big data acquisition and fast processing are required. However, for some physical world applications such as autonomous drone flight, it is difficult to achieve efficient learning because learning with a premature A.I. is dangerous, cost-ineffective, and time-consuming. To solve these problems, simulation-based approaches can be considered. In this study, we analyze recent trends in drone simulation technologies and compare their features. Subsequently, we introduce Octopus, which is a highly precise and scalable drone simulator being developed by ETRI.