• Title/Summary/Keyword: Drone Altitude

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Implementation of Radar Drone Detection Based on ISAR Technique (ISAR 영상 기반 소형 드론 탐지 구현)

  • Lee, Kee-Woong;Song, Kyoung-Min;Song, Jung-Hwan;Jung, Chul-Ho;Lee, Woo-kyung;Lee, Myeong-Jin;Song, Yong-Kyu
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.28 no.2
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    • pp.159-162
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    • 2017
  • Along with the popular use of commercial drones, there are increased concerns on the possible threats from drones intruding into secured areas. The difficulty of drone detection is attributed to its stealthy operation flying at low altitude with low level signature. Consequently, the anti-drone technique has been of major research topic in recent years and among others, the radar detection is considered as the most promising technique. However, the use of conventional radar detection may not be effective due to the low level radar cross sections of the commercial drones. In this paper, ISAR technique has been employed to implement drone detection in urban area. To this purpose, a pulsed radar system is set up on the ground to track flying drones and the corresponding ISAR images are produced by coherent processing.

A study on the establishment and utilization of large-scale local spatial information using search drones (수색 드론을 활용한 대규모 지역 공간정보 구축 및 활용방안에 관한 연구)

  • Lee, Sang-Beom
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.1
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    • pp.37-43
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    • 2022
  • Drones, one of the 4th industrial technologies that are expanding from military use to industrial use, are being actively used in the search missions of the National Police Agency and finding missing persons, thereby reducing interest in a wide area and the input of large-scale search personnel. However, legal review of police drone operation is continuously required, and the importance of advanced system for related operations and analysis of captured images in connection with search techniques is increasing at the same time. In this study, in order to facilitate recording, preservation, and monitoring in the concept of precise search and monitoring, it is possible to achieve high efficiency and secure golden time when precise search is performed by constructing spatial information based on photo rather than image data-based search. Therefore, we intend to propose a spatial information construction technique that reduces the resulting data volume by adjusting the unnecessary spatial information completion rate according to the size of the subject. Through this, the scope of use of drone search missions for large-scale areas is advanced and it is intended to be used as basic data for building a drone operation manual for police searches.

Analysis of Low Altitude Wind Profile Data from Wind Lidar for Drone Aviation Safety (드론의 안전 비행을 위한 윈드라이다 저고도 바람 분석 방법 제시)

  • Kim, Je-Won;Ryu, Jung-Hee;Na, Seong-Jun;Seong, Seong-Cheol
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.50 no.12
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    • pp.899-907
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    • 2022
  • According to the Unmanned aircraft system Traffic Management (UTM), drones are permitted to fly up to 150m above ground, which is located in the atmospheric boundary layer where there is considerable wind fluctuation due to turbulence. Although it is difficult to predict when turbulence will occur drone aviation safety could be enhanced by having a better understanding of the characteristics of vertical profile of wind in the flight area. We used wind lidar (WIndMast 350M) to observe vertical profiles of wind at the test site for aviation meteorological observation equipment located near Incheon International Airport in July and September, 2022. In this study, we utilized the observed wind profile data to propose a technique for obtaining information that could help improve the drone aviation safety. The Fourier transform analysis is used to evaluate the temporal characteristics of the horizontal wind speed at various vertical levels up to 350m. We also examined the relative contribution of the variance of wind having scales of less than an hour, a crucial scale for drone flight, to the variance of wind having all scales at each vertical altitude for days with and without precipitation.

Development of a Motor Speed Controller of Drones Considering Voltage Drop of Battery (배터리 전압 강하를 고려한 드론 모터 속도 제어기 개발)

  • Lee, Sunghee;Yun, Bo Ram;Kim, Deok Yeop;Kim, Hwangsoo;Lee, Woo Jin
    • Journal of KIISE
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    • v.44 no.6
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    • pp.601-606
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    • 2017
  • Recently, we have frequently encountered flying drones with the growth of drone industry. However, it is difficult for a driver to stabilize the motor speed of drones, since the voltage of a Lithium polymer battery used in drones may suddenly drop or rise when its power is exhausted. The instability of the motor speed precludes the drone from maintaining a flight altitude, so that the fuselage of a drone performs ascending and descending repeatedly. For solving this problem, existing techniques either add a compensator considering voltage drop of battery or change the control model. Since these techniques use hardware-implemented modules or depend on motor type and experimental results, there is a problem that new suitable modules should be implemented in accordance with the used motor of the fuselage. For solving this problem, in this paper, we implement a motor speed controller in the firmware of drones by considering voltage drop of battery to enhance drone flight stability.

Simulation of The Effective Distribution of Droplets and Numerical Analysis of The Control Drone-Only Nozzle (방제드론 전용노즐의 유효살포폭 내 액적분포 및 수치해석 시뮬레이션)

  • Jinteak Lim;Sunggoo Yoo
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.2
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    • pp.531-536
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    • 2024
  • Control drones, which are recently classified as smart agricultural machines in the agricultural field, are striving to build smart control and automatic control systems by combining hardware and software in order to shorten working hours and increase the effectiveness of control in the aging era of rural areas. In this paper, the characteristics of the nozzle dedicated to the control drone were analyzed as a basic study for the establishment of management control and automatic control systems. In order to consider various variables such as the type of various drone models, controller, wind, flight speed, flight altitude, weather conditions, and UAV pesticide types, related studies are needed to be able to present the drug spraying criteria in consideration of the characteristics and versatility of the nozzle. Therefore, to enable the consideration of various variables, flow analysis (CFD) simulation was conducted based on the self-designed nozzle, and the theoretical and experimental values of the droplet distribution were compared and analyzed through water reduction experiments. In the future, we intend to calculate accurate scattering in consideration of various variables according to drone operation and use it in management control and automatic control systems.

Comparison of Deep-Learning Algorithms for the Detection of Railroad Pedestrians

  • Fang, Ziyu;Kim, Pyeoungkee
    • Journal of information and communication convergence engineering
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    • v.18 no.1
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    • pp.28-32
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    • 2020
  • Railway transportation is the main land-based transportation in most countries. Accordingly, railway-transportation safety has always been a key issue for many researchers. Railway pedestrian accidents are the main reasons of railway-transportation casualties. In this study, we conduct experiments to determine which of the latest convolutional neural network models and algorithms are appropriate to build pedestrian railroad accident prevention systems. When a drone cruises over a pre-specified path and altitude, the real-time status around the rail is recorded, following which the image information is transmitted back to the server in time. Subsequently, the images are analyzed to determine whether pedestrians are present around the railroads, and a speed-deceleration order is immediately sent to the train driver, resulting in a reduction of the instances of pedestrian railroad accidents. This is the first part of an envisioned drone-based intelligent security system. This system can effectively address the problem of insufficient manual police force.

Research for Carbon Dioxide Fluctuation using Drone above the Mud Flat and Reed Beds in the Suncheon Bay (드론 관측을 통한 순천만 갯벌과 갈대밭 상부 대기의 이산화탄소 농도 분포 연구)

  • Kang, Dong-hwan;Jo, Won Gi;Yun, Yeon Su;Yu, Hun Sun;Jang, Seon Woong;Kim, Dong Lib;Park, Jeong Hwan;Song, Young Chul;Choi, Yong Jae
    • Journal of Environmental Science International
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    • v.29 no.7
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    • pp.703-713
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    • 2020
  • In this study, carbon dioxide concentration and air temperature at different elevations were observed and analyzed in the upper atmosphere of mud flat and reed beds at low tide in Suncheon Bay. The carbon dioxide concentration and air temperature sensors were mounted on the drone, and the carbon dioxide concentration and air temperature by altitude (5 m, 10 m, 20 m, 40 m) at five points in the tidal flat and reed beds were observed in the morning and afternoon. The carbon dioxide concentrations in the upper atmosphere of the tidal flat ranged from 453.0 to 460.2 ppm in the morning and 441.6 to 449.7 ppm in the afternoon. The carbon dioxide concentrations in the upper atmosphere of the reed beds ranged from 448.9 to 452.4 ppm in the morning and 446.0 to 454.4 ppm in the afternoon. The carbon dioxide concentrations in the upper atmosphere of the tidal flat was higher in the morning than in the afternoon, and the carbon dioxide concentration decreased as the altitude increased. The carbon dioxide concentration in the upper atmosphere of the reed beds was similar in the morning and afternoon at all altitudes, and the carbon dioxide concentration decreased as the altitude increased. The correlation coefficient between carbon dioxide concentration and air temperature observed in the tidal flat in the morning was -0.54 ~ -0.77, and the correlation coefficient between carbon dioxide concentration and air temperature observed in the afternoon was 0.56 ~ 0.80. The correlation coefficient between carbon dioxide concentration and temperature observed in the morning in the reed field was low, below 0.3, and the correlation coefficient between carbon dioxide concentration and air temperature observed in the afternoon was 0.35 ~ 0.77. In the upper atmosphere of the tidal flats and reed beds, the linear function was suitable for the change of carbon dioxide concentration as a air temperature, and the coefficient of determination of the estimated linear function was higher in the afternoon than in the morning. Through this study, it was confirmed that the carbon dioxide concentration in the upper atmosphere of the tidal flat and the reed beds was different, and the increase rate of carbon dioxide concentration in the upper atmosphere of the tidal flat and the reed beds was higher in the afternoon than in the morning.

Strategic Cattle Roundup using Multiple Quadrotor UAVs

  • Jung, Sunghun;Ariyur, Kartik B.
    • International Journal of Aeronautical and Space Sciences
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    • v.18 no.2
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    • pp.315-326
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    • 2017
  • Four quadrotor UAVs are maneuvered to guide four animals into their pen within the minimum time by creating noises of predators modeled with an exponential function. The quadrotor UAVs are controlled via PID controllers, follow time optimal trajectories, and avoid collisions through altitude separations. The stability of the proposed PID controller is analyzed and verified using MATLAB/Simulink based simulations. Proposed step by step strategies would be practical solutions of actual cattle roundup problems.

A Study on the Direction finding of Drones Using Apollonius Circle Technique (Apollonius Circle 기법을 활용한 드론 방향탐지 연구)

  • Choi, Hong-Rak;Jeong, Won-Ho;Kim, Kyung-Seok
    • 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.

Discriminant analysis to detect fire blight infection on pear trees using RGB imagery obtained by a rotary wing drone

  • Kim, Hyun-Jung;Noh, Hyun-Kwon;Kang, Tae-Hwan
    • Korean Journal of Agricultural Science
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    • v.47 no.2
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    • pp.349-360
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    • 2020
  • Fire-blight disease is a kind of contagious disease affecting apples, pears, and some other members of the family Rosaceae. Due to its extremely strong infectivity, once an orchard is confirmed to be infected, all of the orchards located within 100 m must be buried under the ground, and the sites are prohibited to cultivate any fruit trees for 5 years. In South Korea, fire-blight was confirmed for the first time in the Ansung area in 2015, and the infection is still being identified every year. Traditional approaches to detect fire-blight are expensive and require much time, additionally, also the inspectors have the potential to transmit the pathogen, Thus, it is necessary to develop a remote, unmanned monitoring system for fire-blight to prevent the spread of the disease. This study was conducted to detect fire-blight on pear trees using discriminant analysis with color information collected from a rotary-wing drone. The images of the infected trees were obtained at a pear orchard in Cheonan using an RGB camera attached to a rotary-wing drone at an altitude of 4 m, and also using a smart phone RGB camera on the ground. RGB and Lab color spaces and discriminant analysis were used to develop the image processing algorithm. As a result, the proposed method had an accuracy of approximately 75% although the system still requires many flaws to be improved.