• Journal of Korean Society of Coastal and Ocean Engineers
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• 제29권3호
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• pp.162-168
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• 2017

Shallow-water bathymetry survey has been conducted using high definition color images obtained at the altitude of 100 m above sea level using a drone. Shallow-water bathymetry data are one of the most important input data for the research of beach erosion problems. Especially, accurate bathymetry data within closure depth are critically important, because most of the interesting phenomena occur in the surf zone. However, it is extremely difficult to obtain accurate bathymetry data due to wave-induced currents and breaking waves in this region. Therefore, optical remote sensing technique using a small drone is considered to be attractive alternative. This paper presents the potential utilization of image processing algorithms using multi-variable linear regression applied to red, green, blue and grey band images for estimating shallow water depth using a drone with HD camera. Optical remote sensing analysis conducted at Wolpo beach showed promising results. Estimated water depths within 5 m showed correlation coefficient of 0.99 and maximum error of 0.2 m compared with water depth surveyed through manual as well as ship-board echo-sounder measurements.

• Journal of Advanced Navigation Technology
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• 제26권5호
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• pp.304-311
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• 2022

Although the SEAD(suppression to enemy air defenses) mission is a strategically important task in modern warfare, the high risk of direct exposure to enemy air defense assets forces to use of unmanned aerial vehicles. this paper proposes a path planning algorithm for SEAD mission for an unmanned aerial vehicle and a method for calculating the mission effectiveness on the planned path. Based on the RRT-based path planning algorithm, a low-altitude ingress/egress flight path that can consider the enemy's short-range air defense threat was generated. The Dubins path-based Intercept path planning technique was used to generate a path that is the shortest path while avoiding the enemy's short-range anti-aircraft threat as much as possible. The ingress/intercept/egress paths were connected in order. In addition, mission effectiveness consisting of fuel consumption, the survival probability, the time required to perform the mission, and the target destruction probability was calculated based on the generated path. The proposed techniques were verified through a scenario.

• Journal of the Korea institute for structural maintenance and inspection
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• 제27권5호
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• pp.30-39
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• 2023

Large dams, which are critical infrastructures for disaster prevention, are exposed to various risks such as aging, floods, and earthquakes. Better dam safety inspection and diagnosis using digital transformation technologies are needed. Traditional visual inspection methods by human inspectors have several limitations, including many inaccessible areas, danger of working at heights, and know-how based subjective inspections. In this study, drone photogrammetry was performed on two large dams to evaluate the applicability of digital data-based dam safety inspection and propose a data management methodology for continuous use. High-quality 3D digital models with GSD (ground sampling distance) within 2.5 cm/pixel were generated by flat double grid missions and manual photography methods, despite reservoir water surface and electromagnetic interferences, and severe altitude differences ranging from 42 m to 99.9 m of dam heights. Geometry profiles of the as-built conditions were easily extracted from the generated 3D mesh models, orthomosaic images, and digital surface models. The effectiveness of monitoring dam deformation by photogrammetry was confirmed. Cracks and deterioration of dam concrete structures, such as spillways and intake towers, were detected and visualized efficiently using the digital 3D models. This can be used for safe inspection of inaccessible areas and avoiding risky tasks at heights. Furthermore, a methodology for mapping the inspection result onto the 3D digital model and structuring a relational database for managing deterioration information history was proposed. As a result of measuring the labor and time required for safety inspection at the SYG Dam spillway, the drone photogrammetry method was found to have a 48% productivity improvement effect compared to the conventional manpower visual inspection method. The drone photogrammetry-based dam safety inspection is considered very effective in improving work productivity and data reliability.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제21권4호
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• pp.259-267
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• 2020

This study measured the Particulate Matter (PM) concentration according to altitude (30 m, 60 m, 90 m, 120 m, and 150 m) in three different environments: a construction site, natural environment (arboretum), and residential area. PM_2.5 and PM₁₀ values at 30 m above the construction site were 18.63 ㎍/㎥ and 24.23 ㎍/㎥ while values at 150 m were 10.89 ㎍/㎥ and 10.61 ㎍/㎥, respectively, indicating the average concentration decreased as altitude increased. PM_2.5 and PM₁₀ values at 30 m above the natural environment were 9.03 ㎍/㎥ and 11.21 ㎍/㎥ while those at 150 m were 3.42 ㎍/㎥ and 3.57 ㎍/㎥, respectively, showing lower average concentrations as altitude increased. PM_2.5 and PM₁₀ values at 30 m above the residential area were 10.65 ㎍/㎥ and 12.06 ㎍/㎥ while those at 150 m were 4.24 ㎍/㎥ and 5.17 ㎍/㎥, also demonstrating lower PM concentrations as altitude increased. The PM concentrations decreased as altitude increased at all tested sites and also decreased between environments in the following order: construction site, residential area, and natural environment. The results of this study are significant because PM concentrations were measured at various altitudes at different land-use sites. The results are expected to serve as basic data for decision-making in both regional and urban planning.

• Proceedings of the Korea Information Processing Society Conference
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• 한국정보처리학회 2017년도 춘계학술발표대회
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• pp.653-656
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• 2017

드론에서 고도유지 비행을 위해 정확한 고도 측정이 필요하다. 고도 측정을 위해 많이 사용되는 가속도센서는 변화에 민감하여 거리 측정에 적합하지만 적분 오차가 누적되어 거리 측정값이 발산한다. 또한 드론 비행 시 드론에서 발생하는 진동을 드론의 고도 변화로 잘못 인지하는 문제가 있다. 이 문제를 해결하기 위해 상용화된 드론이나 기존 연구들은 가속도센서를 기반으로 다른 센서나 장치를 추가하여 고도 측정을 하지만 실제 비행 시 고도의 오차가 나타난다. 또한 센서 값들의 연산처리가 많아져 고도 측정 속도가 지연될 우려가 있다. 따라서 다른 센서나 장치를 추가하지 않고 드론의 특성을 고려한 보다 정확한 고도 측정 방안이 필요하다. 본 논문에서는 가속도센서를 이용하여 드론 비행 특성을 고려하는 고도 측정 알고리즘을 제안한다. 실험으로 제안 알고리즘을 수행하여 드론 비행 시 고도 측정의 정확성이 향상됨을 보인다.

• Journal of Advanced Navigation Technology
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• 제28권3호
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• pp.375-378
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• 2024

The instrument landing system (ILS) is an international standard established by the International civil aviation organization (ICAO) as one of the landing support facilities for aircraft. This system consists of a localizer (LOC) that provides orientation information about the runway to indicate the approach direction, a glide path (GP) that indicates the appropriate approach glide slope, and three of marker beacons (MB) that indicates the distance to the runway landing edge. In this study, we predicted the received signal strength by altitude and distance for LOC signals transmitted from the ground and analyzed the difference with the signal strength measured in the actual environment. Our objective is to develop signal strength prediction technology and apply it to the real environment.

• Journal of Advanced Navigation Technology
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• 제21권6호
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• pp.554-560
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• 2017

Accurate altimetry is required for the reliable flight control of drones or unmanned air vehicles (UAVs), and the radar altimeter is commonly used owing to its accuracy for the ground level. Due to the limitation for size, weight and power consumption, the frequency modulated continuous wave (FMCW) radar is appropriate for drone because it has lower complexity than that of pulse Doppler (PD) radar. Especially, fast-ramp FMCW radar, which transmits linear FM signal during very short period, is generally utilized, because it is robust for the ego-motion of drone. Therefore, we present the design and implementation results of the radar signal processor (RSP) for fast-ramp FMCW radar system. The proposed RSP was designed with Verilog-HDL and implemented with Altera Cyclone-IV FPGA device. Implementation results show that the proposed RSP includes 27,523 logic elements, 15,798 registers and memory of 138Kbits and can measure the altimeter at the rate of 100Hz with the operating frequency of 50MHz.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• 제16권6호
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• pp.90-100
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• 2017

The purpose of this study is to detect and label the vehicles using the drone images as a way to overcome the limitation of the existing point and section detection system and vehicle gap estimation on Arterial road. In order to select the appropriate time zone, position, and altitude for the acquisition of the drone image data, the final image data was acquired by shooting under various conditions. The vehicle was detected by applying mixed Gaussian, image binarization and morphology among various image analysis techniques, and the vehicle was labeled by applying Kalman filter. As a result of the labeling rate analysis, it was confirmed that the vehicle labeling rate is 65% by detecting 185 out of 285 vehicles. The gap was calculated by pixel unitization, and the results were verified through comparison and analysis with Daum maps. As a result, the gap error was less than 5m and the mean error was 1.67m with the preceding vehicle and 1.1m with the following vehicle. The gaps estimated in this study can be used as the density of the urban roads and the criteria for judging the service level.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제19권11호
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• pp.497-505
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• 2018

In a situation where the amount of bulky waste needs to be quantified, a three-dimensional model of the wastes can be constructed using drones. This study constructed a drone-based 3D model with a range of flight parameters and a GCPs survey, analyzed the relationship between the accuracy and time required, and derived a suitable drone application technique to estimate the amount of waste in a short time. Images of waste were photographed using the drone and auto-matching was performed to produce a model using 3D coordinates. The accuracy of the 3D model was evaluated by RMSE calculations. An analysis of the time required and the characteristics of the top 15 models with high accuracy showed that the time required for Model 1, which had the highest accuracy with an RMSE of 0.08, was 954.87 min. The RMSE of the 10th 3D model, which required the shortest time (98.27 min), was 0.15, which is not significantly different from that of the model with the highest accuracy. The most efficient flight parameters were a high overlapping ratio at a flight altitude of 150 m (60-70% overlap and 30-40% sidelap) and the minimum number of GCPs required for image matching was 10.

• Korean Journal of Remote Sensing
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• 제35권2호
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• pp.203-215
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• 2019

As hyperspectral sensors that can be mounted on drones are developed, it is possible to acquire hyperspectral imagery with high spatial and spectral resolution. Although the importance of atmospheric correction has been reduced since imagery of drones were acquired at a low altitude,studies on the conversion process from raw data to spectral reflectance should be done for studies such as estimating the concentration of surface materials using hyperspectral imagery. In this study, a vicarious radiometric calibration and an atmospheric correction algorithm based on atmospheric radiation transfer model were applied to hyperspectral data of drone and the results were compared and analyzed. The vicarious calibration method was applied to an empirical line calibration using the spectral reflectance of a tarp made of uniform material. The atmospheric correction algorithm used ATCOR-4 based Modran-5 that was widely used for the atmospheric correction of aerial hyperspectral imagery. As a result of analyzing the RMSE of the difference between the reference reflectance and the correction, the vicarious calibration using the tarp in a single period of hyperspectral image was the most accurate, but the atmospheric correction was possible according to the application purpose of using hyperspectral imagery. If the correction process of normalized spectral reflectance is carried out through the additional vicarious calibration for imagery from multiple periods in the future, accurate analysis using hyperspectral drone imagery will be possible.