• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.627-635
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• 2019

A programmable drone is a drone developed not only to experience the basic principles of flight but also to control drones through Arduino-based programming. Due to the nature of the training drones, the main users are students who are inexperienced in controlling the drones, which often cause frequent collisions with external objects, resulting in high damage to the drones' frame. In this study, the structural stability of the drone was evaluated by means of a structural dynamics based collision simulation for educational drone frame. Collision simulations were performed on three cases according to the impact angle of $0^{\circ}$, $+15^{\circ}$ and $-15^{\circ}$, using an analytical model with approximately 240,000 tetrahedron elements. Using ANSYS LS-DYNA, which provides excellent functions for the simulation of the dynamic behavior of three-dimensional structures, the stress distribution and strain generated on the drone upper, the drone lower, and the ring assembly were analyzed when the drones collided against the wall at a rate of 4 m/s. Safety factors resulting from the equivalent stress and the yield strain were calculated in the range of 0.72 to 2.64 and 1.72 to 26.67, respectively. To ensure structural stability for areas where stress exceeds yield strain and ultimate strain according to material properties, the design reinforcement is presented.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.9
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• pp.973-978
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• 2015

The drone delivery service as a new important business is emerging worldwide. American DHL parcel service is already running the delivery business using drones, and the Google, Amazon, and china's Alibaba, Baidu are also preparing for the same business. However, there are some problems in security and safety since the heavy parcels flies over the people walking down streets, so many things must be considered. The problems can be solved by communicating among drones to avoid collision. Therefore, the efficient network performance is essential, and to resolve the problem, in this paper, an efficient routing protocol is suggested by the Opnet simulator. The drone intercommunication network of MANET is designed and simulated for the efficient routing protocol.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.107-112
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• 2018

Recently, there are many real life applications that uses drones. There are various applications such as the aerial shot with the drones for the broadcasting service or drone racing competition and so on. Specifically, they patrol for the traffic enforcement on a highway. The police department use the 'Spot Mobility' method which float the drones for 30 minute period. However, this method is inefficient for the wide area with small numbers of enforcement. Therefore, a wireless network system consists of drones to patrol on the highway systematically is required. In this paper, the most efficient routing protocol will be selected for the MANET drone network by applying various routing protocols. To accomplish this, the drone patrol network system with routing protocols are designed and simulated in OPNET simulator.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.1
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• pp.53-61
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• 2021

This paper is a preliminary study for the development of a drone for inspection inside a boiler in a thermal power plant, which is a high-temperature environment, and validated whether the drone can fly normally through a high-temperature environment simulation using AirSim. In a high-temperature flight environment, the aerodynamic characteristics of the air density and viscosity are different from room temperature, and the flight performance of the drone is also changed accordingly. Therefore, in order to confirm the change of the aerodynamic characteristics of the propeller according to the temperature change, the propeller analysis and thrust test through JBLADE, and the operation characteristics prediction through the electric propulsion system performance prediction model were performed. In addition, the analysis and performance prediction results were applied to AirSim for simulation, and the aircraft redesigned through the analysis of the results. As a result of the redesign, it was confirmed that about 65% of the maximum power used before the redesign was reduced to 52% to obtain the necessary thrust when hovering in an environment of 80℃.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.3
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• pp.173-180
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• 2022

The operation and transportation environment for an unmanned aerial vehicle will be completely different from those for the conventional air and ground transportation. The requirement for a traffic management system for its safe operation has been emerging. Accordingly, investigation is being conducted to analyze the danger that unmanned aerial vehicle may encounter during the flight and to provide the countermeasure by the simulation. When the drones operate in an urban environment, they may be affected by the wind around the building. Thus it is essential to predict the influence of the gust and analyze the resulting risk. In this paper, a method for evaluating the safety for a flight mission under the gust is suggested. By using the precise 6-degree-of-freedom flight simulation that is capable of simulating the gust condition, possible deviation from the pre-planned flight path in terms of the attitude orientation will be predicted. A method of quantifying the probability of the flight mission failure will also be presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1220-1226
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• 2021

In this paper, we propose a probabilistic handover scheme for enhancing spectral efficiency in drone-based wireless communication systems. When a moving drone base station (DBS) provides the drone-based wireless communication service to a user equipment (UE) located on the ground, our proposed handover scheme considers the distance between DBS and UE and small scale fading. In addition, our proposed handover scheme considers a handover probability to mitigate the signalling overhead that may occur when performing frequent handovers. Through simulations for drone-based wireless communication systems, we evaluate the spectral efficiency and the handover probability of our proposed handover scheme and the conventional handover scheme. The simulation results show that our proposed handover scheme can achieve higher average spectral efficiency than the conventional handover scheme which considers only the distance between DBS and UE.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.342-345
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• 2019

드론의 동작 검증을 위한 테스트는 최종적으로 드론이 운용될 환경에서 이루어진다. 그러나 테스트 비용이 크고 테스트 비행 중 파손의 위험이 있기 때문에 시뮬레이션을 통한 사전 검증을 수행하는 것이 중요하다. 시뮬레이션은 SIL 방식이나 HIL 방식으로 이루어지는데 추가적인 외부 센서를 활용하는 경우 검증하기가 어렵다. SIL에서는 검증을 위해 가상의 외부 센서 구현이 필요하다. HIL 에서는 실제 센서를 사용하므로 가상의 외부 센서 구현은 필요 없다. 그러나 테스트 환경이기 때문에 실제 환경과 비슷한 데이터나 동작 검증에 적합한 데이터를 얻기 어렵다. 이러한 HIL에서의 문제를 해결하기 위해 외부 센서를 실제 환경에서 사용한 로그나 테스트 환경에서 센서 검증에 사용한 로그를 이용할 수 있다. 본 논문에서 제안하는 외부 센서의 로그를 활용한 HIL 시뮬레이션 기법 확장 내용은 외부 센서 데이터 입력기가 로그로부터 얻은 센서 데이터를 비행 컨트롤러로 보내 검증을 수행하기 때문에 데이터를 재사용할 수 있고 테스트 비용을 줄일 수 있다. 또 외부 센서 데이터 입력기는 로그 파서, 뷰어, 슬라이서, 데이터 전송기로 구성되어 로그로부터 검증에 적합한 데이터를 쉽게 얻어 활용할 수 있다.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1451-1466
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• 2023

In the context of maritime emergencies, the utilization of drones has rapidly increased, with a particular focus on their application in search and rescue operations. Deep learning models utilizing drone images for the rapid detection of distressed vessels and other maritime drift objects are gaining attention. However, effective training of such models necessitates a substantial amount of diverse training data that considers various weather conditions and vessel states. The lack of such data can lead to a degradation in the performance of trained models. This study aims to enhance the performance of deep learning models for distress ship detection by developing a maritime environment simulator to augment the dataset. The simulator allows for the configuration of various weather conditions, vessel states such as sinking or capsizing, and specifications and characteristics of drones and sensors. Training the deep learning model with the dataset generated through simulation resulted in improved detection performance, including accuracy and recall, when compared to models trained solely on actual drone image datasets. In particular, the accuracy of distress ship detection in adverse weather conditions, such as rain or fog, increased by approximately 2-5%, with a significant reduction in the rate of undetected instances. These results demonstrate the practical and effective contribution of the developed simulator in simulating diverse scenarios for model training. Furthermore, the distress ship detection deep learning model based on this approach is expected to be efficiently applied in maritime search and rescue operations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.83-92
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• 2018

This paper uses the Apollonius Circle technique to estimate the position of a target that generates a specific signal by using a drone, which is rapidly becoming a rapidly expanding industry. The existing direction finding method is performed through the vehicle on the ground or installed the antenna at a high position to detect the position of the target. However, the conventional direction finding method is difficult to configure the reception environment of the LOS signal, It is difficult. However, the direction finding using the drone is easy to construct and measure the LOS signal receiving environment using the drone flying at high altitude. In this study, we use the 3D 800MHz Path-Loss Model to reconstruct the signal by using the measurement data of the ground direction finding, reconstruct the signal by using the 3-D 800MHz Path-Loss Model, and use the Apollonius Circle method to estimate the position of the target. A simulation was performed to estimate the position of the target. Simulation was performed to determine the target position estimation performance by configuring the ground direction finding and the dron direction finding.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.97-104
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• 2018

In the conventional direction finding, the antenna is installed at a high position on the ground to detect the position of the target with the environment of the LOS(Line of Sight) as much as the signal receiving environment. However, in order to configure such environment, high cost and installation time were required. In this paper, we use TDOA(Time Difference of Arrival) technique to utilize drones in direction finding, so that four drones can be used for directions finding simulation. Simulations based on drone and TDOA direction finding were constructed using additional signal processing Taylor series and Exact Interactive Algorithm. In the simulation, the receiving power is defined by using the 800MHz path-loss model using the GPS information of the ground direction detection, and the position estimation performance is analyzed when the TDOA technique, the Taylor series, and the Exact Interactive Alogrithm are applied.