• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.81-87
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• 2016

It is important to analyze the exact damage information for fast recovery when natural disasters cause damage on river-side facilities such as dams, bridges, embankments etc. In this study, we shows the method to effectively damage analysis plan using UAV(Unmanned aerial vehicle) images and accuracy assessment of it. The UAV images are captured on area near the river-side facilities and the core methodology for damage analysis are image matching and change detection algorithm. The result(point cloud) from image matching is to construct 3-dimensional data using by 2-dimensional images, it extracts damage areas by comparing the height values on same area with reference data. The results are tested absolute locational precision compared by post-processed aerial LiDAR data named reference data. The assessment analysis test shows our matching results 10-20 centimeter level precision if external orientation parameters are very accurate. This study shows suggested method is very useful for damage analysis in a large size structure like river-side facilities. But the complexity building can't apply this method, it need to the other method for damage analysis.

• Journal of Platform Technology
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• v.8 no.1
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• pp.3-9
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• 2020

In Korea, 63% of the nation's land is made up of forests, and the average temperature of the earth has been increasing. Forest service has been operating a proactive control system for preventing the spread of forest pests such as Pine wilt disease. but there were some hurdles in timely control due to weather, topography and manpower management difficulties. In this paper, we propose a model for building fast, accurate and efficient control system by categorizing the damage and dead wood automatically based on the images acquired using small unmanned aerial vehicles based on information and communication technology. In particular, the proposed model establishes an effective response system for government affairs through cooperation in the private sector. It can also create new jobs in the unmanned aerial vehicle business and service industries.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.5
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• pp.466-474
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• 2020

Semi-active laser missile systems with high accuracy are necessary to asymmetric threats, such as UAV(Unmanned Aerial Vehicle). They are usually used to attack stationary or slow moving targets, therefore we should study on the laser designator which can detect and track fast moving targets in order to deal with UAV. In this study, design specifications are came up through performance analysis of existing laser designators, and laser designation method for fast moving target is developed. The detection and tracking performance of developed laser designator are verified through inside/outside tests on ground/aerial stationary/moving targets. Through this study, we obtain laser designator techniques that could be applied to actual semi-active laser missile systems.

• International Journal of Control, Automation, and Systems
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• v.5 no.1
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• pp.104-109
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• 2007

This paper is about a redundancy management system design for the Smart UAV(unmanned aerial vehicle) which utilizes the tilt..rotor mechanism. In order to meet the safety requirement on the PLOC(probability of loss of control) of $1.7{\times}10^{-5}$ per flight hour for FCS (flight control system) failures, a digital FCS is mechanized with a dual redundant structure. A fault detection system which is composed of a CCM(cross channel monitor) and analytic redundancy using the Kalman filtering is designed, and its effectiveness is evaluated through experiments. A threshold level and persistence count for managing redundant sensors are designed based on the statistical analysis of the FCS sensors. To increase the survivability of the UAV after the loss of critical sensors in the SAS(stability augmentation system) and to provide reference information for a tie-breaking condition at which an ILM(in-line monitor) cannot distinguish the faulty channel between two operating ones, the Kalman filter approach is investigated.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.2
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• pp.213-221
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• 2024

Aircraft's operational effectiveness is reduced due to threats from enemy anti-aircraft weapons, which is a weak point. In particular, guided missiles, which pose a threat to aircraft, are rapidly developing due to technological advancements in seekers, and are classified as one of the important technologies in weapon systems. Missile approach warning equipment installed to ensure aircraft survivability detects guided missiles and provides relevant information to respond. Tests were conducted domestically to verify the detection level of missile approach warning equipment, and test results were presented under various test conditions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.155-163
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• 2019

This paper proposes a new methodology to recognize cracks on asphalt road surfaces using the image data obtained with drones. The target section was Yuseong-daero, the main highway of Daejeon. Furthermore, two object detection algorithms, such as Tiny-YOLO-V2 and Faster-RCNN, were used to recognize cracks on road surfaces, classify the crack types, and compare the experimental results. As a result, mean average precision of Faster-RCNN and Tiny-YOLO-V2 was 71% and 33%, respectively. The Faster-RCNN algorithm, 2Stage Detection, showed better performance in identifying and separating road surface cracks than the Yolo algorithm, 1Stage Detection. In the future, it will be possible to prepare a plan for building an infrastructure asset-management system using drones and AI crack detection systems. An efficient and economical road-maintenance decision-support system will be established and an operating environment will be produced.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.5
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• pp.469-479
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• 2016

Kimchi cabbage is one of the most important vegetables in Korea and a target crop for market stabilization as well. In particular Kimchi cabbages in a highland area are very sensitive to the fluctuations in supply and demand. Yield variability due to growth conditions dictates the market fluctuations of Kimchi cabbage price. This study was carried out to understand the distribution of the highland Kimchi cabbage growth status in Anbandeok. Anbandeok area in Gangneung, Gangwon-do, Korea is one of the main producing districts of highland Kimchi cabbage. The highland Kimchi cabbage status map of each growth factor was obtained from unmanned aerial vehicle (UAV) imagery and field survey data. Six status maps include UAVRGB image map, normalized difference vegetation index (NDVI) distribution/anomaly map, Crop distribution map, Planting/Harvest distribution map, Growth parameter map and Growth disorder map. As a result, the highland Kimchi cabbage status maps from May 31 to Sep. 6 in 2016 were presented to show spatial variability in the field. The benefits of the highland Kimchi cabbage status map can be summarized as follows: crop growth monitoring, reference for field observations and survey, the relative comparison of the growth condition in field scale, evaluation of growth in comparison of average year, change detection of annual crops or planting areas, abandoned fields monitoring, prediction of harvest season etc.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.71-78
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• 2017

Many studies have been implemented to manage solar plant being supplied widely in recent years. This study analyzed heat emission of solar cell using unmanned aerial vehicle(UAV)-based thermal infrared sensor, and major conclusions are as belows. Firstly, orthomosaic image and digital surface model(DSM) data were acquired using UAV-based RGB sensor, and solar light module layer necessary to analyze the heat emission of solar cell was constructed by these data. Also as a result of horizontal error into validation points using virtual reference service(VRS) survey for evaluating the location accuracy of solar light module layer, higher location accuracy could be acquired like standard error of $dx={\pm}2.4cm$ and $dy={\pm}3.2cm$. And this study installed rubber patch to test the heat emission of solar cell and could analyzed efficiently the location of rubber patch being emitted heat using UAV-based thermal infrared sensor. Also standard error showd as ${\pm}3.5%$ in analysis between calculated cell ratio by rubber patch and analyzed cell ratio by UAV-based thermal infrared sensor. Therefore, it could be efficiently analyzed to heat emission of solar cell using UAV-based thermal infrared sensor. Also efficient maintenance of solar plant could be possible through extracting the code of solar light module being emitted of heat automatically.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.5
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• pp.349-357
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• 2022

Since the flight control computer of unmanned aerial vehicle (UAV) is a flight critical equipment, it is necessary to ensure reliability and safety from the development step, and a redundancy-based fault management design is required in order to operate normally even a failure occurs. To reduce cost, weight and power consumption, the dual-redundant flight control system design is considered in UAV. However, there are various restrictions on the fault management design. In this paper, we propose the fault detection and isolation designs for the dual-redundant flight control computer to satisfy the safety requirements of an UAV. In addition, the flight control computer developed by applying the fault management design performed functional tests in the integrated test environment, and after performing FMET in the HILS, its reliability was verified through flight tests.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.10-20
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• 2019

Irregular rainfall caused by climate change, in combination with non-point pollution, can cause water systems worldwide to suffer from frequent eutrophication and algal blooms. This type of water pollution is more common in agricultural prone to water system inflow of non-point pollution. Therefore, in this study, the correlation between Unmanned Aerial Vehicle(UAV) multi-spectral images and total phosphorus, total nitrogen, and chlorophyll-a with indirect association of algal blooms, was analyzed to identify the usability of UAV image to identify water quality characteristics in agricultural streams. The analysis the vegetation index Normalized Differences Index (NDVI), the Normalized Differences Red Edge(NDRE), and the Chlorophyll Index Red Edge(CIRE) for the detection of multi-spectral images and algal blooms collected from the target regions Yang cheon and Hamyang Wicheon. The analysis of the correlation between image values and water quality analysis values for the water sampling points, total phosphorus at a significance level of 0.05 was correlated with the CIRE(0.66), and chlorophyll-a showed correlation with Blue(-0.67), Green(-0.66), NDVI(0.75), NDRE (0.67), CIRE(0.74). Total nitrogen was correlated with the Red(-0.64), Red edge (-0.64) and Near-Infrared Ray(NIR)(-0.72) wavelength at the significance level of 0.05. The results of this study confirmed a significant correlations between multi-spectral images collected through UAV and the factors responsible for water pollution, In the case of the vegetation index used for the detection of algal bloom, the possibility of identification of not only chlorophyll-a but also total phosphorus was confirmed. This data will be used as a meaningful data for counterplan such as selecting non-point pollution apprehensive area in agricultural area.