• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2003.11a
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• pp.203-207
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• 2003

Due to the inherent nature of the low flying UAV, obstacle detection is a fundamental requirement in the flight path to avoid the collision from obstacles as well as manned aircraft. In this paper, a preliminary sensor requirements of an obstacle detection system for UAV in low-altitude flight are analyzed, and the automated obstacle detection sensor system is proposed assessing both passive and active sensors such as EO camera, IR, Laser radar, microwave and millimeter radar. In addition, TCAS (Traffic Alert and Collision Avoidance System) are reviewed for the collision avoidance of the manned aircraft system. It is suggested that small-sized radar sensor is the best candidate for the smart UAV because an active radar can provide the real-time informations on range and range rate in the all-weather environment. However, an important constraints on small UAV should be resolved in terms of accommodation of the mass, volume, and power allocated in the payload of the UAV system design requirements.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.9
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• pp.883-888
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• 2011

The UAV tracking antenna system based on GPS has a characteristic of update of position information which can occurs a position error. To reduce the position error, UAV tracking antenna system separates period of GPS update-rate and predicts the position of UAV using divided time points. These process improves the tracking performance of UAV. To predict the position of UAV by divided time points, we used a linear kalman filter based on the velocity and acceleration. Using this system, we measured velocity and acceleration according to the change of position. Finally, we can predict the change of position on divided time points.

• Journal of the Korea Society for Simulation
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• v.15 no.1
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• pp.43-50
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• 2006

The major objective of this paper is to propose a hybrid simulation environment for autonomous UAV system by integrating the continuous-time model with discrete-event model. Proposed system is able to support high autonomous behavior by combining the planner, recognizer, and controller model to deal with the HL20 AIRPLANE model. Thus, the high level decision may be efficiently issued even upon the unexpected circumstance. The proposed system model has been successfully verified by several simulation test performed on the DEVS simulation S/W environment.

• Journal of Korean Society of Water and Wastewater
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• v.32 no.6
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• pp.573-581
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• 2018

The purpose of this study is to evaluate the fixed wing type domestic UAV for monitoring of algae bloom in aquatic environment. The UAV used in this study is operated automatically in-flight using an automatic navigation device, and flies along a path targeting preconfigured GPS coordinates of desired measurement sites input by a flight path controller. The sensors used in this study were Sequoia multi-spectral cameras. The photographed images were processed using orthomosaics, georeferenced digital surface models, and 3D mapping software such as Pix4D. In this study, NDVI(Normalized distribution vegetation index) was used for estimating the concentration of chlorophyll-a in river. Based on the NDVI analysis, the distribution areas of chlorophyll-a could be analyzed. The UAV image was compared with a airborne image at a similar time and place. UAV images were found to be effective for monitoring of chlorophyll-a in river.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2606-2626
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• 2022

In this paper, a unmanned aerial vehicle (UAV) access deployment algorithm is proposed, which is based on an improved virtual force model to solve the poor coverage quality of UAVs caused by limited number of UAVs and random mobility of users in the deployment process of UAV base station. First, the UAV-adapted Harris Hawks optimization (U-AHHO) algorithm is proposed to maximize the coverage of users in a given hotspot. Then, a virtual force improvement model based on user perception (UP-VFIM) is constructed to sense the mobile trend of mobile users. Finally, a UAV motion algorithm based on multi-virtual force sharing (U-MVFS) is proposed to improve the ability of UAVs to perceive the moving trend of user equipments (UEs). The UAV independently controls its movement and provides follow-up services for mobile UEs in the hotspot by computing the virtual force it receives over a specific period. Simulation results show that compared with the greedy-grid algorithm with different spacing, the average service rate of UEs of the U-AHHO algorithm is increased by 2.6% to 35.3% on average. Compared with the baseline scheme, using UP-VFIM and U-MVFS algorithms at the same time increases the average of 34.5% to 67.9% and 9.82% to 43.62% under different UE numbers and moving speeds, respectively.

• ETRI Journal
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• v.45 no.2
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• pp.240-253
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• 2023

Spatial information is geometrical information combined with the properties of an object. In city areas where unmanned aerial vehicle (UAV) usage demand is high, it is necessary to determine the appropriate driving altitude considering the height of buildings for safe driving. In this study, we propose a data-provision method that generates the driving altitude of UAVs with a pseudo-3D building model. The pseudo-3D building model is developed using high-precision spatial information provided by the National Geographic Information Institute. The proposed method generates the driving altitude of the UAV in terms of tile information, including the UAV's starting and arrival points and a straight line between the two points, and provides the data to users. To evaluate the efficacy of the proposed method, UAV driving altitude information was generated using data of 763 551 pseudo-3D buildings in Seoul. Subsequently, the generated driving altitude data of the UAV was verified in AirSim. In addition, the execution time of the proposed method and the calculated driving altitude were analyzed.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.8-19
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• 2023

This paper presents advancement in multi- unmanned aerial vehicle (UAV) cooperative area surveillance, focusing on optimizing UAV route planning through the application of genetic algorithms. Addressing the complexities of comprehensive coverage, two real-time dynamic path planning methods are introduced, leveraging genetic algorithms to enhance surveillance efficiency while accounting for flight constraints. These methodologies adapt multi-UAV routes by encoding turning angles and employing coverage-driven fitness functions, facilitating real-time monitoring optimization. The paper introduces a novel path planning model for scenarios where UAVs navigate collaboratively without predetermined destinations during regional surveillance. Empirical evaluations confirm the effectiveness of the proposed methods, showcasing improved coverage and heightened efficiency in multi-UAV path planning. Furthermore, we introduce innovative optimization strategies, (Foresightedness and Multi-step) offering distinct trade-offs between solution quality and computational time. This research contributes innovative solutions to the intricate challenges of cooperative area surveillance, showcasing the transformative potential of genetic algorithms in multi-UAV technology. By enabling smarter route planning, these methods underscore the feasibility of more efficient, adaptable, and intelligent cooperative surveillance missions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.779-800
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• 2024

Unmanned Aerial Vehicle (UAV) networks, also known as drone networks, have gained significant attention for their potential in various applications, including communication. UAV networks for communication involve using a fleet of drones to establish wireless connectivity and provide communication services in areas where traditional infrastructure is lacking or disrupted. UAV communication networks need to be highly secured to ensure the technology's security and the users' safety. The proposed survey provides a comprehensive overview of the current state-of-the-art UAV network security solutions. In this paper, we analyze the existing literature on UAV security and identify the various types of attacks and the underlying vulnerabilities they exploit. Detailed mitigation techniques and countermeasures for the protection of UAVs are described in this paper. The survey focuses on the implementation of novel technologies like Q-learning, blockchain, IRS, and mmWave. This paper discusses network simulation tools that range in complexity, features, and programming capabilities. Finally, future research directions and challenges are highlighted.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.453-464
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• 2019

Recently, as the demand for 3D geospatial information increases, the importance of rapid and accurate data construction has increased. Although many studies have been conducted to register UAV (Unmanned Aerial Vehicle) imagery based on LiDAR (Light Detection and Ranging) data, which is capable of precise 3D data construction, studies using LiDAR data embedded in MMS (Mobile Mapping System) are insufficient. Therefore, this study compared and analyzed 9 matching algorithms based on feature points for registering reflectance image converted from LiDAR point cloud intensity data acquired from MMS with image data from UAV. Our results indicated that when the SIFT (Scale Invariant Feature Transform) algorithm was applied, it was able to stable secure a high matching accuracy, and it was confirmed that sufficient conjugate points were extracted even in various road environments. For the registration accuracy analysis, the SIFT algorithm was able to secure the accuracy at about 10 pixels except the case when the overlapping area is low and the same pattern is repeated. This is a reasonable result considering that the distortion of the UAV altitude is included at the time of UAV image capturing. Therefore, the results of this study are expected to be used as a basic research for 3D registration of LiDAR point cloud intensity data and UAV imagery.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.1-6
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• 2020

UAV (Unmanned Aerial Vehicles) are used widely for military purposes because they are more economical than general manned aircraft and satellites, and have easy access to the object. Recently, owing to the development of IT technology, UAV equipped with various sensors have been released, and their use is increasing in a wide range of fields, such as surveying, agriculture, meteorological observation, communication, broadcasting, and sports. An increasing number of studies and attempts have made use of it. On the other hand, existing research was related mostly to photogrammetry, but there has been a lack of analytical research on LiDAR (Light Detection And Ranging). Therefore, this study examined the characteristics of a UAV LiDAR sensor for the application of a geospatial information field. In this study, the performance of commercialized LiDAR sensors, such as the acquisition speed and the number of echoes, was investigated, and data acquisition and analysis were conducted by selecting Surveyor Ultra and VX15 models with similar accuracy and data acquisition distances. As a result, a DSM of each study site was generated for each sensor, and the characteristics of data density, precision, and acquisition of ground data from vegetation areas were presented through comparison. In addition, the UAV LiDAR sensor showed an accuracy of 0.03m ~ 0.05m. Hence, it is necessary to select equipment considering the characteristics of data for effective use. In the future, the use of UAV LiDAR may be suggested if additional data can be obtained and analyzed for various areas, such as urban areas and forest areas.