• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.367-371
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• 2004

This paper describes development of automatic flight control system for an unmanned target drone which is operated by Korean army as for anti-air gun shooting training. Current target drone is operated by pilot control of on-board servo motor via remote control system. Automatic flight control system for the target drone greatly reduces work load of ground pilot and can increase application area of the drone. Most UAVs being operated now days use high-priced sensors as AHRS and IMU to measure the attitude, but those are costly. This paper introduces the development of low-cost automatic flight control system with low-cost sensors. The integrated automatic flight control system has been developed by integrating combining power module, switching module, monitoring module and RC receiver as an one module. The performance of automatic flight control system is verified by flight test.

• Journal of Advanced Navigation Technology
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• v.8 no.2
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• pp.105-111
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• 2004

This paper describes the design of navigation system for an unmanned target drone which is operated by Korean army as for anti-air gun shooting training. Current target drone is operated by pilot control of on-board servo motor via remote control system. Automatic flight control system for the target drone greatly reduces work load of ground pilot and can increase application area of the drone. Most UAVs being operated nowdays use high-priced sensors as AHRS and IMU to measure the attitude, but those are costly. This paper introduces the development of low-cost automatic flight control system with low-cost sensors. The integrated automatic flight control system has been developed by integrating combining power module, switching module, monitoring module and RC receiver as an one module. The performance of navigation for low cost unmanned aerial vehicle, unmanned target drone as our test bed in this paper is verified by both Hardware in the loop simulation(HILS) to test performance of GPS as GPS output frequency high and results of flight test.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.3
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• pp.193-200
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• 2016

This paper introduces an algorithm to middle-low price drone's autonomous navigation flight system using computer vision and GPS. Existing drone operative system mainly contains using methods such as, by inputting course of the path to the installed software of the particular drone in advance of the flight or following the signal that is transmitted from the controller. However, this paper introduces new algorithm that allows autonomous navigation flight system to locate specific place, specific shape of the place and specific space in an area that the user wishes to discover. Technology developed for military industry purpose was implemented on a lower-quality hobby drones without changing its hardware, and used this paper's algorithm to maximize the performance. Camera mounted on middle-low price drone will process the image which meets user's needs will look through and search for specific area of interest when the user inputs certain image of places it wishes to find. By using this algorithm, middle-low price drone's autonomous navigation flight system expect to be apply to a variety of industries.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.230-232
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• 2019

There is an accelerating need for ocean sensing where autonomous vehicles can play a key role in assisting engineers, researcher and scientists with environmental monitoring and collecting oceanographic data. This paper is performed to develops an autonomous sailing drone to be used as a sensor carrying platform for autonomous data acquisition at Sea. From a sailing drone design viewpoint, it is important to establish reliable prediction methods for sailing drone's resistance. The required power for the propulsion unit depends on the ship resistance and speed. There are three solutions for the prediction of ship resistance as follow analytical methods, model tests in tanks and Computational Fluid Dynamics (CFD). The present paper aims at simulating sailing drone friction resistance using numerical method. The dynamic mesh motion is used to describe the sailing drone movement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.8
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• pp.936-942
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• 2019

Autonomous driving of drone indoor must move along a narrow path and overcome other factors such as lighting, topographic characteristics, obstacles. In addition, it is difficult to operate the drone in the hallway because of insufficient texture and the lack of its diversity comparing with the complicated environment. In this paper, we study an autonomous drone navigation using Convolution Neural Network(CNN) in indoor environment. The proposed method receives an image from the front camera of the drone and then steers the drone by predicting the next path based on the image. As a result of a total of 38 autonomous drone navigation tests, it was confirmed that a drone was successfully navigating in the indoor environment by the proposed method without hitting the walls or doors in the hallway.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.600-602
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• 2022

This paper proposes an algorithm that cancels the jamming and interference in the 433 MHz band promoted by the Ministry of Science and ICT at the physical layer level so that the drone operation distance can be extended up to 20 km.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.685-689
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• 2023

The proposed system in the study aims to detect forest fires in real-time stream data received from the drone-camera. Recently, the number of wildfires has been increasing, and also the large scaled wildfires are frequent more and more. In order to prevent forest fire damage, many experiments using the drone camera and vision analysis are actively conducted, however there were many challenges, such as network speed, pre-processing, and model performance, to detect forest fires from real-time streaming data of the flying drone. Therefore, this study applied image data processing works to capture five good image frames for vision analysis from whole streaming data and then developed the object detection model based on YOLO_v2. As the result, the classification model performance of forest fire images reached upto 93% of accuracy, and the field test for the model verification detected the forest fire with about 70% accuracy.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.243-251
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• 2021

Real-Time Kinematic (RTK) is a phase-based differential GNSS technique and uses additional observations from permanent reference stations to mitigate or eliminate effects like atmospheric delays or satellite clocks and orbit errors. In particular, as the position accuracy required in the fields of autonomous vehicles and drones is gradually increasing, the demand for RTK-based precise navigation that can provide cm-level position is increasing. Recently, with the rapid growth of the open-source software market, the use of open-source software for building navigation system of unmanned vehicles, which is difficult to mount an expensive GNSS receivers, is gradually increasing. RTKLIB is an open-source software package that can perform RTK positioning and is widely used for research and education purposes. However, since the performance and stability of RTK algorithm of RTKLIB is inevitably inferior to that of commercial GNSS receivers, users need to verify whether RTKLIB can satisfy the navigation performance requirements of unmanned vehicles. Therefore, in this paper, the performance evaluation of the RTK positioning algorithm of RTKLIB was performed using GNSS observation data acquired in a dynamic environment. Therefore, in this paper, the RTK positioning performance of RTKLIB was evaluated using GNSS observation data acquired in a dynamic environment. Our results show that the current RTK algorithm of RTKLIB is not suitable for precise navigation of unmanned vehicles.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.458-464
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• 2020

Drones are being spreaded for the purposes such as construction, logistics, scientific research, recording, toy and so on. However, anti-drone related technologies which make the opposite drones neutralized are also widely being researched and developed because some drones are being used for crime or terror. The range of anti-drone related technologies can be divided into detection, identification and neutralization. The drone neutralization methods are divided into Soft-kill one which blocks the detected drones using jamming and Hard-kill one which destroys the detected ones physically. In this paper, Google and Naver domestic news articles related to anti-drone were gathered. Analyzing the domestic news articles, 8 of related technologies using RF, GNSS, Radar and so on were found. Regarding as this, the general features and usage status of those technologies were described and those on anti-drone for each company and agency were gathered and analyzed.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.491-499
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• 2020

There are policies that foster the drone industry, which either put a legal precedent on drones through the "Drone Act" or grant a delay or exemption in applying the safety measures of "the Aviation Safety Act". Yet, the definition of a drone is unclear, requiring further discussion on commercial usage. Therefore, we have studied cases domestically and abroad, and also analyzed issues with the current aviation legislation. It was found that a drone is defined as "an unmanned aircraft where a pilot is not on board, and its net weight is 150 kg or less". However, there are several issues, such as that a drone taxi requires a pilot on board, and its weight is 150 kg or more. Thus, we propose to define a drone as "an unmanned aerial vehicle (provided, that its own net weight should be 300 kg or under, or not be limited to weight) under Article 2 (3) of the "Aviation Security Act" as prescribed by Ordinance of the Ministry of Land, Infrastructure, and Transport, which operates either by remote, automatically, or autonomously; or an unmanned aircraft under Article 2 (6) of the "Aviation Security Act".