• Aerospace Engineering and Technology
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• v.11 no.2
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• pp.73-79
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• 2012

Because the contact time between satellite and ground station is very limited in LEO (Low Earth Orbit) satellite, all telemetry data generated on spacecraft bus are stored in a mass memory and downlinked to the ground together with real time data during the contact time. The mass memory is initialized in the first system initialization phase and the page status of each memory block is generated step by step. After the completion of the system initialization, the telemetry data are continuously stored and the stored data are played back to the ground by command. And the memory scrubbing is periodically performed for correction of single bit error which can be generated on harsh space environment. This paper introduces the mass memory operation method for telemetry processing of LEO satellite. It includes a general mass memory data structure, the methods of mass memory initialization, scrubbing, data storage and downlink, and mass memory management of primary and redundant mass memory.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.257-268
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• 2024

Drone-mounted hyperspectral sensors (DHSs) have revolutionized remote sensing in agriculture by offering a cost-effective and flexible platform for high-resolution spectral data acquisition. Their ability to capture data at low altitudes minimizes atmospheric interference, enhancing their utility in agricultural monitoring and management. This study focused on addressing the challenges of radiometric and geometric distortions in preprocessing drone-acquired hyperspectral data. Radiometric correction, using the empirical line method (ELM) and spectral reference panels, effectively removed sensor noise and variations in solar irradiance, resulting in accurate surface reflectance values. Notably, the ELM correction improved reflectance for measured reference panels by 5-55%, resulting in a more uniform spectral profile across wavelengths, further validated by high correlations (0.97-0.99), despite minor deviations observed at specific wavelengths for some reflectors. Geometric correction, utilizing a rubber sheet transformation with ground control points, successfully rectified distortions caused by sensor orientation and flight path variations, ensuring accurate spatial representation within the image. The effectiveness of geometric correction was assessed using root mean square error(RMSE) analysis, revealing minimal errors in both east-west(0.00 to 0.081 m) and north-south directions(0.00 to 0.076 m).The overall position RMSE of 0.031 meters across 100 points demonstrates high geometric accuracy, exceeding industry standards. Additionally, image mosaicking was performed to create a comprehensive representation of the study area. These results demonstrate the effectiveness of the applied preprocessing techniques and highlight the potential of DHSs for precise crop health monitoring and management in smart agriculture. However, further research is needed to address challenges related to data dimensionality, sensor calibration, and reference data availability, as well as exploring alternative correction methods and evaluating their performance in diverse environmental conditions to enhance the robustness and applicability of hyperspectral data processing in agriculture.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.45-45
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• 2017

On-site monitoring of vegetable growth parameters, such as leaf length, leaf area, and fresh weight, in an agricultural field can provide useful information for farmers to establish farm management strategies suitable for optimum production of vegetables. Unmanned Aerial Vehicles (UAVs) are currently gaining a growing interest for agricultural applications. This study reports on validation testing of previously developed vegetable growth estimation models based on UAV-based RGB images for white radish and Chinese cabbage. Specific objective was to investigate the potential of the UAV-based RGB camera system for effectively quantifying temporal and spatial variability in the growth status of white radish and Chinese cabbage in a field. RGB images were acquired based on an automated flight mission with a multi-rotor UAV equipped with a low-cost RGB camera while automatically tracking on a predefined path. The acquired images were initially geo-located based on the log data of flight information saved into the UAV, and then mosaicked using a commerical image processing software. Otsu threshold-based crop coverage and DSM-based crop height were used as two predictor variables of the previously developed multiple linear regression models to estimate growth parameters of vegetables. The predictive capabilities of the UAV sensing system for estimating the growth parameters of the two vegetables were evaluated quantitatively by comparing to ground truth data. There were highly linear relationships between the actual and estimated leaf lengths, widths, and fresh weights, showing coefficients of determination up to 0.7. However, there were differences in slope between the ground truth and estimated values lower than 0.5, thereby requiring the use of a site-specific normalization method.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.1
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• pp.49-62
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• 2005

The VR (virtual reality) simulator such as helicopter simulation needs virtual environment of existing urban area. But the real urban environment keeps changing. We need a modeling method to make use of the GIS data that are updated periodically. The flight simulation needs to visualize not only buildings in near distance but also a large number of buildings in the far distance. We propose a method for modeling urban environment from aerial image and digital map with a comparatively small manual work. Image based modeling is applied to urban model which considers the characteristic of Korean cities. Buildings in the distance can be presented without creating a lot of polygons. Proposed method consists of the pre-processing stage which prepares the model from the GIS data and the modeling stage which makes the virtual urban environment. The virtual urban environment can be modeled with the simple process which utilizes the height map of buildings.

• Korean Journal of Environmental Agriculture
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• v.34 no.3
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• pp.230-237
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• 2015

BACKGROUND: To identify the sources of inaccuracy in LC/MS/MS methods used in the routine quantitation of small molecules are described and discussed. METHODS AND RESULTS: Various UPLC coupled to triple quadrupole mass spectrometer and time of flight (TOF) were used to identify the potential sources of inaccuracy and inducing the pitfalls of qualification and quntitation during the veterinary drug residue analysis. Some of stable isotope labelled veterinary drugs, which were used as internal standards, presented "cross-talk", regardless of manufactures of mass spectrometer and types of spectrometer. Group of sulfonamides also presented inaccuracy qualification and quantitation due to the multi-residue analytical method with the same fragment ions at the close retention times. CONCLUSION: The phenomena of "cross-talk" occurring between subsequently monitored transition from stable isotope labelled and isotope non-labelled authentic chemical were identified. To prevent errors and achieve more accurate data during the analysis of small molecules by LC/MS/MS SRM method, Followings should be taken care of and kept checking; purity and concentration of stable isotope as an internal standard, prevention of carry-over during the separation in column, minimizing the ion suppression by matrix effect, identification of retention time, precursor ion and product ion, and full knowledge of data processing including smoothing and peak integration.

• Aerospace Engineering and Technology
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• v.3 no.1
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• pp.222-231
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• 2004

LCS(Launch Control System) in Space Center performs the ground and flight tests of launch vehicle. Those tests require data monitoring and control functions to the external systems such as launch vehicle, launch pad, and propellant supply system, etc. The LCS is composed of real time control system, simulation system, data server, external network, etc. The purpose of the simulation system is to simulate launch vehicle, and it is used for evaluation test of the LCS. This paper described the simulation system overview, the concept design, and the real time data processing evaluation tests of the simulator, gateway, data distribution server which are constituents of the simulation system.

• Journal of Convergence for Information Technology
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• v.9 no.11
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• pp.118-124
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• 2019

As Unmanned Aerial Vehicles technology has been widespread, various types of unmanned aircraft and mission equipment have been developed in line with mission diversification. Especially in Korea, small unmanned aerial vehicles have been actively developed. In addition, flight control system and mission equipment interface system for effective control of small unmanned aerial vehicles, efficient communication system configuration and operation for transmission to ground operated systems by processing data are required. This paper addresses efficient system structure and operation of communication equipment for missions and control of small unmanned aerial vehicles.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_3
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• pp.1325-1332
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• 2023

Recently, much research is being conducted based on point cloud data for the growth of innovations such as construction automation in the transportation field and virtual national space. This data is often measured through remote control in terrain that is difficult for humans to access using devices such as UAVs and UGVs. Drones, one of the UAVs, are mainly used to acquire point cloud data, but photogrammetry using a vision camera, which takes a lot of time to create a point cloud map, is difficult to apply in construction sites where the terrain changes periodically and surveying is difficult. In this paper, we developed a point cloud mapping system by adopting non-repetitive scanning LiDAR and attempted to confirm improvements through field application. For accuracy analysis, a point cloud map was created through a 2 minute 40 second flight and about 30 seconds of software post-processing on a terrain measuring 144.5 × 138.8 m. As a result of comparing the actual measured distance for structures with an average of 4 m, an average error of 4.3 cm was recorded, confirming that the performance was within the error range applicable to the field.

• The Journal of Korean Institute of Information Technology
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• v.17 no.10
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• pp.57-63
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• 2019

Motion errors which are caused by several reasons, non-ideal path, errors of navigation systems, and radar system errors, have to be corrected. Motion compensation methods can compensate the motion error, but not exactly. To correct these residual errors, several autofocus methods are invented. A popular method is phase gradient autofocus (PGA). PGA does not assume specific circumstances, such as isolated point targets and shapes of errors. PGA is an iterative and adaptive method, so that the processing time is the main problem for the real time processing. In this paper, the improved method to select targets for PGA is proposed to reduce processing time. The variances of image pixels are used to select targets with high SNR. The processing of PGA with these targets diminishes the processing time and iterations effectively. The processed results with real radar data, obtained by flight tests, show that the proposed method compensates errors well, and reduce working time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.8-17
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• 2011

Recently, fusion camera systems that consist of depth sensors and color cameras have been widely developed with the advent of a new type of sensor, time-of-flight (TOF) depth sensor. The physical limitation of depth sensors usually generates low resolution images compared to corresponding color images. Therefore, the pre-processing module, such as camera calibration, three dimensional warping, and hole filling, is necessary to generate the high resolution depth map that is placed in the image plane of the color image. However, the result of the pre-processing step is usually inaccurate due to errors from the camera calibration and the depth measurement. Therefore, in this paper, we present a depth map upsampling method robust these errors. First, the confidence of the measured depth value is estimated by the interrelation between the color image and the pre-upsampled depth map. Then, the detailed depth map can be generated by the modified kernel regression method which exclude depth values having low confidence. Our proposed algorithm guarantees the high quality result in the presence of the camera calibration errors. Experimental comparison with other data fusion techniques shows the superiority of our proposed method.