• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.235-242
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• 2021

Unmanned Aerial Vehicles (UAVs), which were used for military purposes, are gradually expanding their application fields under the influence of electrification and digitalization. Starting from the field of aerial imaging and Intelligence Surveillance and Reconnaissance (ISR) mission, nowadays the possibility of Urban Air Mobility (UAM), which transports passengers and cargo with drones, is widely under discussion. In order to occupy the rapidly growing global unmanned aerial vehicle market in advance, it is necessary to secure core technologies and develop key UAVs components based on the new technologies. In the navigation field, it is necessary to secure a precise position with guaranteed reliability and continuity, unrelated to the operating environments. The reliability and continuity should be secured in the algorithm level and in the H/W component levels also. In order to achieve this technical goal, the Ministry of Science and ICT has launched the 'Unmanned Vehicle Core Technology Research and Development Program' in 2019 to support the R&D on the unmanned vehicle technologies. In this paper, authors introduce the unmanned vehicle core technology research and development program to the related researchers. The authors summarize the backgrounds of the program and show the technological tasks and objectives on the sub-programs in the unmanned vehicle navigation program. We present the program schedules especially focused on the test and evaluation of the developed technologies and components.

• Journal of the Society of Disaster Information
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• v.15 no.3
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• pp.427-439
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• 2019

Purpose: We generated geospatial information of unmanned aerial vehicle based on various SW and analyzed the location accuracy of orthoimage and DSM and texture mapping of 3D mesh. Method: The same unmanned aerial image data is processed using two different SW, and spatial information is generated. Among the generated spatial information, the orthoimage and DSM were compared with the spatial information generation results of the unmanned aerial photogrammetry SW by performing quantitative analysis by calculating RMSE of horizontal position and vertical position error and performing qualitative analysis. Results: There were no significant differences in the positional accuracy of the orthoimage and DSM generated by each SW, and differences in texture mapping in 3D mesh. The creation of the 3D mesh indicated the impact of the Unmanned Aerial Photogrammetry SW. Conclusion: It is shown that there is no effect of SW on the creation of orthoimage and DSM for geospatial analysis based on unmanned aerial vehicle. However, when 3D visualization is performed, texture mapping results are different depending on SW.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.207-214
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• 2020

Currently, the operation of unmanned aerial vehicle (UAV) is regulated to be able to fly only within the visible range, but in recent years, the needs for operation in the invisible area, in the urban area and at night have increased. In order to operate UAVs in the invisible area, at night, and in the urban area, a flight path for UAVs must be prepared like those operated by manned aircraft, and for this, it is necessary to establish an unmanned aircraft system traffic management (UTM). In order to establish the UTM, information on the minimum separation distance to prevent collisions with UAVs and buildings is required, and accordingly, information on the navigation performance of UAVs is required. In order to analyze the navigation performance of an UAV, total system error (TSE), which is the difference between the planned flight path and the actual location of the UAV, is required. If the collected data are insufficient and classification according to integrity, independence, and direction is not performed, accurate navigation performance is not derived. In this paper, propose a navigation performance analysis method of UAV that is derived TSE using flight data and modeled with normal distribution, analyze performance.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.2
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• pp.54-66
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• 2007

Traffic and emergency monitoring systems are essential constituents of Intelligent Transportation System (ITS) technologies, but the lack of traffic monitoring has become a primary weakness in providing prompt emergency services. Demonstrated in numerous military applications, unmanned aerial vehicles (UAVs) have great potentials as a part of ITS infrastructure for providing quick and real-time aerial video images of large surface area to the ground. Despite of obvious advantages of UAVs for traffic monitoring and many other civil applications, it is rare to encounter success stories of UAVs in civil application including transportation. The objective of this paper is to report the outcomes of research supported by the state agency in US to investigate the feasibility of integrating UAVs into urban highway traffic monitoring as a part of ITS infrastructure. These include current technical and regulatory issues, and possible suggestions for a future UAV system in civil applications.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1181-1188
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• 2014

In this paper, we propose a novel concept foran unmanned delivery service using a cooperative heterogeneous unmanned system consisting of a self-driving car and an unmanned aerial vehicle (UAV). The proposed concept is suitable to deliver parcels in high-density and high-rise urban or residential areas. In order to achieve the proposed concept, we will develop acooperative heterogeneous unmanned system. Customers can order goods using a smartphone application and the order information, including the position of the customer and the order time, and the package is transported automatically by the unmanned systems. The system assigns the tasks suitable for each unmanned vehicle by analyzing it based on map information. Performance is validated by experiments consisting of autonomous driving and flight tests in a real environment. For more evaluation, the landing position error analysis is performed using circular error probability (CEP).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.555-562
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• 2021

Recently, in the field of geospatial information construction, unmanned aerial vehicles have been increasingly used because they enable rapid data acquisition and utilization. In this study, photogrammetry was performed using fixed-wing, rotary-wing, and VTOL (Vertical Take-Off and Landing) unmanned aerial vehicles, and geospatial information was constructed using two types of unmanned aerial vehicle LiDAR (Light Detection And Ranging) sensors. In addition, the accuracy was evaluated to present the utility of spatial information constructed through unmanned aerial photogrammetry and LiDAR. As a result of the accuracy evaluation, the orthographic image constructed through unmanned aerial photogrammetry showed accuracy within 2 cm. Considering that the GSD (Ground Sample Distance) of the constructed orthographic image is about 2 cm, the accuracy of the unmanned aerial photogrammetry results is judged to be within the GSD. The spatial information constructed through the unmanned aerial vehicle LiDAR showed accuracy within 6 cm in the height direction, and data on the ground was obtained in the vegetation area. DEM (Digital Elevation Model) using LiDAR data will be able to be used in various ways, such as construction work, urban planning, disaster prevention, and topographic analysis.

• Journal of the Korean Geotechnical Society
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• v.38 no.7
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• pp.39-47
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• 2022

This study aims at evaluating the stability of disaster risks, such as schools, apartments, and geotechnical structures located around slopes in urban areas. The research conducted an aerial photography analysis on where the slope of the retaining wall behind 𐩒𐩒 High School in Gwangju collapsed in August 2018 due to heavy rain. In general, the overflow of rainwater has been managed through drainage channels around slopes during the rainy season, and the surface flow of rainfall was limited due to the presence of dense forests in the area. However, when the slope collapsed, a lot of water flowed out of the ground, and the saturated surface layer ground was destroyed. To analyze the cause, the changed terrain of the upper slope area, which could not be directly identified, was photographed using unmanned aerial vehicles. Digital Elevation Model by unmanned aerial vehicle shooting was performed by analyzing the slope map, calculating the direction of rainfall and the length and width of water-logged areas. The change in the instability of the slope over time due to a 10-day rainfall was also analyzed through numerical analysis.

• ETRI Journal
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• v.45 no.5
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• pp.811-821
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• 2023

We propose an adaptive unmanned aerial vehicle (UAV)-assisted object recognition algorithm for urban surveillance scenarios. For UAV-assisted surveillance, UAVs are equipped with learning-based object recognition models and can collect surveillance image data. However, owing to the limitations of UAVs regarding power and computational resources, adaptive control must be performed accordingly. Therefore, we introduce a self-adaptive control strategy to maximize the time-averaged recognition performance subject to stability through a formulation based on Lyapunov optimization. Results from performance evaluations on real-world data demonstrate that the proposed algorithm achieves the desired performance improvements.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.71-91
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• 2018

In recent years, application of UAV(Unmanned Aerial Vehicle) to seed sowing and pest control has been actively carried out in the field of agriculture. In this study, UAS(Unmanned Aerial System) is constructed by combining image sensor of various wavelength band and SfM((Structure from Motion) based image analysis technique in UAV. Utilization of UAS based vegetation survey was investigated and the applicability of precision farming was examined. For this purposes, a UAS consisting of a combination of a VIS_RGB(Visible Red, Green, and Blue) image sensor, a modified BG_NIR(Blue Green_Near Infrared Red) image sensor, and a TIR(Thermal Infrared Red) sensor with a wide bandwidth of $7.5{\mu}m$ to $13.5{\mu}m$ was constructed for a low cost UAV. In addition, a total of ten vegetation indices were selected to investigate the chlorophyll, nitrogen and water contents of plants with visible, near infrared, and infrared wavelength's image sensors. The images of each wavelength band for the test area were analyzed and the correlation between the distribution of vegetation index and the vegetation index were compared with status of the previously surveyed vegetation and ground cover. The ability to perform vegetation state detection using images obtained by mounting multiple image sensors on low cost UAV was investigated. As the utility of UAS equipped with VIS_RGB, BG_NIR and TIR image sensors on the low cost UAV has proven to be more economical and efficient than previous vegetation survey methods that depend on satellites and aerial images, is expected to be used in areas such as precision agriculture, water and forest research.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.117-127
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• 2018

The author tried to propose the orthographic and DTM (digital terrain model) creation and evaluate the accuracy for an university campus using UAV (unmanned aerial vehicle) system. Most previous studies used GPS-based data, but in this paper, the observations of triangulation level measurements was used for comparison of accuracy. Accuracy analysis results showed that the operational requirements for aerial photographic standards are satisfied in all scenaries. The author confirmed availability in aviation photo measurements and applications using UAV (Drone). In order to create a sophisticated DTM and contour, we need to eliminate interference from building, trees, and artificial objects. The results of this study are expected to be used as the basis for future studies in the creation of DTM and the accuracy assessments using Drone.