• Journal of Electrical Engineering and Technology
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• v.7 no.1
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• pp.132-140
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• 2012

A non-conservative robust Kalman filter (NCRKF) is applied to flight data to identify the aerodynamic derivatives of an unmanned autonomous vehicle (UAV). The NCRKF is formulated using UAV lateral motion data and then compared with results from the conventional Kalman filter (KF) and the recursive least square (RLS) method. A superior performance for the NCRKF is demonstrated by simulation and real flight data. The NCRKF is especially effective in large uncertainties in vehicle modeling and in measuring flight data. Thus, it is expected to be useful in missile and aircraft parameter identification.

• Advances in aircraft and spacecraft science
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• v.1 no.2
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• pp.219-232
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• 2014

This paper reports on an ongoing study investigating the feasibility of using an evolutionary method to develop the rules governing Self-Organised (SO) systems for use in swarms of unmanned aerial vehicles. In general, it is difficult to design swarm systems that follow explicit global behaviour. Unlike optimising a predefined objective function, the solution to the problem is the emergent behaviour in the SO systems which results from simultaneous interactions among agents and between agents and their environment. In this study, evolutionary algorithms are used to investigate their control and effectiveness in synthesising the weighting of different rules on SO emergent behaviour. Both homogeneous swarms and heterogeneous swarms were considered though the results provided are for a case study investigating the simplest problem a homogeneous swarm without mutation. Though simple this study does indicate the potential of the approach.

• Journal of the Korean Society of Propulsion Engineers
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• v.5 no.3
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• pp.87-99
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• 2001

Technical status and prospect of the subsonic airbreathing propulsion system composed of jet engine fuel feeding system and air intake for missile application is described herein, including analysis of some present airbreathing missiles. Comprehension on this can be applicable both to blow deeply about the same type missiles and to get some basic idea of unmanned air vehicle's and light aircraft's propulsion system.

• Journal of Aerospace System Engineering
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• v.3 no.3
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• pp.17-23
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• 2009

KARI SUAV (Smart Unmanned Aerial Vehicle) program is currently on the phase of ground and flight test. SUAV is a tilt rotor aircraft having the capability of vertical take-off/landing and high speed forward flight. The SUAV rotor system is 3-bladed, gimbaled hub type, which is not common for conventional helicopter configuration. In this paper, detailed procedure and method of rotor pitch rigging, tracking and balancing were described based on the experience of SUAV ground test.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.327-333
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• 2019

Wind speed data constitute important weather information for aircrafts flying at low altitudes, such as drones. Currently, the accuracy of low altitude wind predictions is much lower than that of high-altitude wind predictions. Deep neural networks are proposed in this study as a method to improve wind speed forecast information. Deep neural networks mimic the learning process of the interactions among neurons in the brain, and it is used in various fields, such as recognition of image, sound, and texts, image and natural language processing, and pattern recognition in time-series. In this study, the deep neural network model is constructed using the wind prediction values generated by the numerical model as an input to improve the wind speed forecasts. Using the ground wind speed forecast data collected at the Boseong Meteorological Observation Tower, wind speed forecast values obtained by the numerical model are compared with those obtained by the model proposed in this study for the verification of the validity and compatibility of the proposed model.

• ETRI Journal
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• v.40 no.6
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• pp.788-793
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• 2018

3D reconstruction of urban architecture, land, and roads is an important part of building a "digital city." Unmanned aerial vehicles (UAVs) are gradually replacing other platforms, such as satellites and aircraft, in geographical image collection; the reason for this is not only lower cost and higher efficiency, but also higher data accuracy and a larger amount of obtained information. Recent 3D reconstruction algorithms have a high degree of automation, but their computation time is long and the reconstruction models may have many voids. This paper decomposes the object into multiple regional parallel reconstructions using the clustering principle, to reduce the computation time and improve the model quality. It is proposed to detect the planar area under low resolution, and then reduce the number of point clouds in the complex area.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.156-157
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• 2018

본 논문에서 제안하는 기술은 무인기 획득 영상에 dense optical flow 기술을 적용하여, 이미지 내에서 급격히 움직이는 사물을 추출하는 기술이다. 제안 기술을 활용하여 사람, 사물 장소에 해당하는 시간에 따른 데이터인 다중로그 데이터로 융합 분석하여 낙석, 산사태, 비탈면 붕괴등을 감지 할 수 있게 되어 보행자의 안전을 보장 하고자 한다. 본 논문에서는 해당 기술을 구현하기 위한 무인기 및 탑재 장비와 데이터 처리를 위한 서버들간의 인터페이스 및 분석 알고리즘을 소개한다.

• Journal of Advanced Engineering and Technology
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• v.11 no.4
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• pp.273-277
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• 2018

In the field of forest disaster prevention, drones are expected to save higher human resources than the existing manpower has, and produce high-efficiency results over time. However, operational limitations brought by short flight times have brought the environment of limited use of the various capabilities of the drone, and the existing development systems operating the multi-drone are mainly for performance purpose, so it is a difficult to use for forest disaster prevention. The purpose of this paper is to design the concept based on multi-drone operation procedure through analysis of mission of ground control system for forest disaster prevention.

• Electronics and Telecommunications Trends
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• v.38 no.3
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• pp.1-10
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• 2023

In this study, the status of global advanced air mobility (AAM) was investigated to derive information and communications technologies (ICTs) that should be prepared according to directions of domestic AAM development. AAM is an urban air traffic system for moving from city to city by electric vertical take-off and landing or personal aircraft. It is expected to establish a three-dimensional air traffic system that can solve ground traffic congestion caused by the rapid global urbanization. With the full-scale commercialization of AAM solutions, high-density air traffic is expected, and with the advent of the personal air vehicle (PAV), the flight space usage is expected to expand. Therefore, it is necessary to develop a safe AAM service through early research on core ICTs for autonomous flight.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.381-388
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• 2023

Small-scale environmental impact assessments have limitations in terms of survey duration and evaluation resources, which can hinder the assessment and analysis of the current situation. In this study, we propose the use of drone technology during the environmental impact assessment process to supplement these limitations in the current situation analysis. Drone photography can provide rapid and accurate high-resolution images, allowing for the collection of various information about the target area. This information can include different types of data such as terrain, vegetation, landscape, and real-time 3D spatial information, which can be collected and processed using GIS software to understand and analyze the environmental conditions. In this study, we confirmed that terrain and vegetation analysis and prediction of the target area using drone photography and GIS analysis software is possible, providing useful information for environmental impact assessments.