• Journal of the Institute of Convergence Signal Processing
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• v.20 no.3
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• pp.171-176
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• 2019

Drones are highly utilized because they can efficiently acquire long-distance videos. In drone operation, the speed, which is the magnitude of the velocity, can be set, but the moving direction cannot be set, so accurate information about the drone's movement should be estimated. In this paper, we estimate the velocity of the drone moving at a constant speed and direction. In order to estimate the drone's velocity, the displacement of the target frame to minimize the sum of absolute difference (SAD) of the reference frame and the target frame is obtained. The ground truth of the drone's velocity is calculated using the position of a certain matching point over all frames. In the experiments, a video was obtained from the drone moving at a constant speed at a height of 150 meters. The root mean squared error (RMSE) of the estimated velocities in x and y directions and the RMSE of the speed were obtained showing the reliability of the proposed method.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.3
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• pp.209-215
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• 2022

As intelligent autonomous driving vehicle development has become a big topic around the world, accurate reference dynamics estimation has been more important than before. Current systems generally use speed and heading information sensed from a distant point as a vehicle reference dynamic, however, the dynamics between different points are not same especially during rotating motions. In order to estimate properly estimate the reference dynamics from the information such as velocity and heading sensed at a point distant from the reference point such as center of gravity, this study proposes estimating reference dynamics from any location in the vehicle by combining the Bicycle and Ackermann models. A test system was constructed by implementing multiple GNSS/INS equipment on an Robot Operating System (ROS) and an actual car. Angle and speed errors of 10° and 0.2 m/s have been reduced to 0.2° and 0.06 m/s after applying the suggested method.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.136-150
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• 2022

In this study, a comparative review was conducted on how to use RGB images to obtain river topographic information, which is one of the most essential data for eco-friendly river management and flood level analysis. In terms of the topographic information of river zone, to obtain the topographic information of flow section is one of the difficult topic, therefore, this study focused on estimating the river topographic information of flow section through RGB images. For this study, the river topography surveying was directly conducted using ADCP and RTK-GPS, and at the same time, and orthomosiac image were created using high-resolution images obtained by drone photography. And then, the existing developed regression equations were applied to the result of channel topography surveying by ADCP and the band values of the RGB images, and the channel bathymetry in the study area was estimated using the regression equation that showed the best predictability. In addition, CCHE2D flow modeling was simulated to perform comparative verification of the topographical informations. The modeling result with the image-based topographical information provided better water depth and current velocity simulation results, when it compared to the directly measured topographical information for which measurement of the sub-section was not performed. It is concluded that river topographic information could be obtained from RGB images, and if additional research was conducted, it could be used as a method of obtaining efficient river topographic information for river management.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.16-16
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• 2021

전자파표면유속계(Microwave Water Surface Current Meter)를 이용한 홍수기 유량측정은 교량과 같은 구조물을 이용하여 안전 및 측정위치의 흐름조건 등의 이유로 측정의 한계가 발생한다. 이런 문제점을 개선하기 위해 전자파표면유속계를 드론(Drone)과 결합하여 하천에서의 유량측정에 이용하였다. 전자파표면유속계는 비접촉식 유속측정 장비로 하천의 표면유속을 측정하고 유량산정을 위해 환산계수 0.85를 적용하여 평균유속을 산정하고 있다. 환산계수 0.85는 하천의 각 횡측선 수심-유속분포를 일반적인 분포로 가정하고 표면유속에 0.85를 곱하여 평균유속을 산정한다(Rantz, 1982). 그러나 하천의 측정위치 및 흐름특성에 따라 유속분포가 변화하기 때문에 국외 많은 연구에서 환산계수의 범위를 0.72에서 1.72까지 제시한 바 있다(Johnson and Cowen, 2017). 따라서 환산계수 0.85의 일률적인 적용은 부정확한 유량산정을 초래할 수 있어 측정위치에 적절한 환산계수 산정이 필요하다. 본 연구에서는 2020년 금강의 지류인 봉황천에 위치한 금산군(황풍교) 관측소에서 드론과 전자파표면유속계를 이용해 측정한 표면유속과 ADCP를 이용하여 동시 측정한 평균유속의 비교를 통해 환산계수를 산정하여 평균유속 산정의 정확도를 높이고자 하였다. 전자파표면유속계로 측정한 6개 성과 중 ADCP와 동시 측정한 4개의 성과를 분석하여 환산계수를 산정하였다. 측정성과별 측선수는 16~17개로 홍수터로 월류하여 비정상흐름이 발생한 측선은 제외하고 측선별 환산계수는 0.66에서 1.09의 범위로 나타났고, 성과별 환산계수의 평균치는 0.90에서 0.93 범위로 산정되었다. 환산계수가 일반적인 수치보다 높게 산정된 것은 측정위치 하류 약 600m에 위치한 콘크리트 고정보의 영향이 홍수 시 흐름의 수위-유속분포에 영향을 미쳐 높게 산정된 것으로 판단된다. 따라서 유량산정에 있어 환산계수는 4개 성과에서 산정된 환산계수의 평균치인 0.92를 적용하여 산정하였다.