• 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.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.470-477
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• 2022

EOTS for drones is showing another aspect of market expansion in detection and recognition areas previously occupied by artificial satellites. The two-axis EOTS for drones controls the vibration or disturbance caused by the drone during the mission so that EOTS can accurately recognize the goal. Vibration generated by drones is transmitted to EOTS. Therefore, it is essential to develop a stabilization controller that attenuates vibrations transmitted from drones so that EOTS can maintain the viewing angle. Therefore, it is necessary to standardize drone disturbance and secure the performance of EOTS disturbance attenuation controller optimized for disturbance level through this. In this paper, a method of standardizing drone disturbance applied to EOTS is studied, through which EOTS controller simulation is performed and stabilization controller shape is selected and designed.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.371-377
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• 2021

This research proposes the best combination of tropospheric delay models for Korean Positioning System (KPS). The overall results are based on real observation data of Japanese Quasi-Zenith satellite system (QZSS), whose constellation is similar to the proposed constellation of KPS. The tropospheric delay models are constructed as the combinations of three types of zenith path delay (ZPD) models and four types of mapping functions (MFs). Two sets of International GNSS Service (IGS) stations with the same receiver are considered. Comparison of observation residuals reveals that the ZPD models are more influential to the measurement model rather than MFs, and that the best tropospheric delay model is the combination of GPT3 with 5 degrees grid and Vienna Mapping Function 1 (VMF1). While the bias of observation residual depends on the receivers, it still remains to be further analyzed.

• Annual Conference of KIPS
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• 2022.11a
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• pp.52-54
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• 2022

Aerial images are being one of the important aspects of satellite imagery, delivers effective information on landcovers. Their special characteristics includes the viewpoint from space which clarifies data related to land examining processes. Aerial images taken by satellites employed radio waves to wirelessly transmit images to ground stations. Due to transmission errors, images get distorted and unable to perform in landcover examining. This paper proposes an aerial image enhancement method using deep autoencoders. A properly trained autoencoder can enhance an aerial image to a considerable level of improvement. Results showed that the achieved enhancement is better than that was obtained from traditional image denoising methods.

• Electronics and Telecommunications Trends
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• v.39 no.1
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• pp.48-61
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• 2024

The integration of high-capacity terrestrial networks with non-terrestrial communication using satellites has become essential to support seamless low-latency services based on artificial intelligence and big data. Tunable light sources have been instrumental in resolving the complexity of channel management in wavelength division multiplexing (WDM) systems, contributing to increased network flexibility and serving as optical sources for long-distance coherent systems. Recently, these light sources have been applied to beam-steering devices in laser communication and sensing applications across ground, aerial, and satellite transport. We examine the utilization and requirements of tunable lasers in WDM networks and describe the relevant development status. In addition, performance requirements and development directions for tunable lasers used in optical interference systems and beam-steering devices are reviewed.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.49-56
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• 2020

Detecting shadows in images and restoring or removing them was a very challenging task in computer vision. Traditional researches used color information, edges, and thresholds to detect shadows, but there were errors such as not considering the penumbra area of shadow or even detecting a black area that is not a shadow. Deep learning has been successful in various fields of computer vision, and research on applying deep learning has started in the field of shadow detection and removal. However, it was very difficult and time-consuming to collect data for network learning, and there were many limited conditions for shooting. In particular, it was more difficult to obtain shadow data from buildings and satellite images, which hindered the progress of the research. In this paper, we propose a method for generating shadow data from buildings and satellites using Unity3D. In the virtual Unity space, 3D objects existing in the real world were placed, and shadows were generated using lights effects to shoot. Through this, it is possible to get all three types of images (shadow-free, shadow image, shadow mask) necessary for shadow detection and removal when training deep learning networks. The method proposed in this paper contributes to helping the progress of the research by providing big data in the field of building or satellite shadow detection and removal research, which is difficult for learning deep learning networks due to the absence of data. And this can be a suboptimal method. We believe that we have contributed in that we can apply virtual data to test deep learning networks before applying real data.

• Spatial Information Research
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• v.17 no.1
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• pp.89-102
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• 2009

The information of ocean topology is the fundamental source which is necessary for understanding the ocean, producing nautical charts and delimiting maritime boundaries. An echo sounder is being used generally to collect undersea bathymetric data, but an indirect method such as geophysical data acquired by satellites is being used recently. In this study, the outputs of ocean surveying for the production of the Basic Maps of the Sea in 1996 and 1997 in the East Sea and the bathymetric data produced by geophysical data are compared and analyzed. The study areas are Ulleung Plateau, Ulleung Basin and the southern area of Ulleung Basin which have different geophysical characteristics. Through this study, we found that the bathymetric data acquired by an indirect method using satellite is similar to the field surveying results in general configuration of ocean floor and average depth. However, the minimum square error is about 100m in 1700m depth, and it has been observed a local error up to 1000m. In addition, it has been found that the detailed undulation of ocean topology is shown on the gravity data which is acquired by the research vessel.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.2 s.25
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• pp.39-45
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• 2003

Roads have been developed throughout the history of mankind, and play a significant role among many traffic facilities for the economy, politics and cultures of our lives. However, the management of roads has not been fully scientific or systematic due to governmental policies focused on construction resulting in damages, and the loss of drawings for existing roads. In this case, it is difficult to manage roads using normal cadastre due to its time consuming work. And, when applying satellite surveying to rapidly extract the centerline of roads, it is impossible to obtain data about the status of internal tunnels. Therefore, this study can be used to extract optimum alignment data of tunnels using the data from satellite surveying, and is a practical paper which can contribute to efficient management and usage of alignment data and road facilities in establishing a HMS(Highway Management System) for the renewal and management of the alignment data of roads, by comparing the data from satellites with the alignment data in existing drawings.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.4
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• pp.622-630
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• 2016

In the operation of a low earth orbit satellite, a series of antenna commands are transmitted from a ground station to the satellite within a visibility window (i.e., the time period for which an antenna of the satellite is visible from the station) and executed to control the antenna. The window is a limited resource where all data transmission is carried out. Therefore, minimizing the transmission time for the antenna commands by reducing the data size is necessary in order to provide more time for the transmission of other data. In this paper, we propose a geometric compression method based on B-spline curve fitting using dominant points in order to compactly represent the antenna commands. We transform the problem of command size reduction into a geometric problem that is relatively easier to deal with. The command data are interpreted as points in a 2D space. The geometric properties of the data distribution are considered to determine the optimal parameters for a curve approximating the data with sufficient accuracy. Experimental results demonstrate that the proposed method is superior to conventional methods currently used in practice.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.6
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• pp.851-862
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• 2006

Satellites have been valuable tool for global/regional scale atmospheric environment monitoring as well as emission source detection. In this study, we present the results of application of satellite remote sensing data for air quality forecast in Seoul metropolitan area. AOT (Aerosol Optical Thickness) data from TERRA/MODIS (Moderate Resolution Imaging Spectre-radiometer) satellite were compared to ground based $PM_{10}$ mass concentrations, and used to estimate the possibility of the aerosol forecasting in Seoul metropolitan area. Although correlation coefficient (${\sim}0.37$) between MODIS AOT products and surface $PM_{10}$ concentration data was relatively low, there was good correlation between MODIS AOT and surface PM concentration under certain atmospheric conditions, which supports the feasibility of using the high-resolution MODIS AOT for air quality forecasting. The MODIS AOT data with trajectory forecasts also can provide information on aerosol concentration trend. The success rate of the 24 hour aerosol concentration trend forecast result was about 75% in this study. Finally, application of satellite remote sensing data with ground-based air quality observations could provide promising results for air quality monitoring and more exact trend forecast methodology by high resolution satellite data and verification with long term measurement dataset.