• Aerospace Engineering and Technology
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• v.11 no.1
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• pp.42-48
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• 2012

The telemetry data received from satellite in real-time are used to monitor LEO satellite during the AIT (Assembly, Integration & Test) phase and the mission operation phase after launch. However, it is impossible to check all the incoming telemetry data from satellite in real time in order to detect abnormality of satellite quickly. Especially, the contact time of LEO satellite is limited because of its orbital characteristics. So the anomaly state of the LEO satellite should be detected and resolved during the contact time. Therefore, all incoming spacecraft telemetry data must be selected and manipulated in MIMIC. It is used in order to display summarized information about spacecraft in a visualized way that is quickly and easily understood. That is, it provides essential function to monitor a satellite both in orbit and during testing. In this paper, the design and development of MIMIC currently used in KOMPSAT, a LEO Earth observation satellite is described in detail. In future work, we plan to enhance MIMIC in order to improve user-friendliness and efficiency.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.4
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• pp.45-54
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• 2004

In this paper, a view point tracking system has been realized for outdoor augmented reality including broad area monitoring. Since the surroundings of the moving view point are changing, it is necessary to track the position and observation moment of the view point system for consistency between real and virtual images. For this reason, the GPS(Global Positioning System) is applied to the realized system for tracking the information on position and direction of the moving system. In addition, an optical position tracking system that is able to track view point in a limited area is used, because the local tracking system has to trace the image variation, seen to the observer in a moving vehicle, at a particular position and time. It was found that the realized outdoor augmented reality system, which combined the virtual information tracked in real time with the real image, can be very practical in various application area.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.360-365
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• 2014

There are many types of advanced devices for weather prediction process such as weather radar, satellite, radiosonde, and other weather observation devices. Among them, the weather radar is an essential device for weather forecasting because the radar has many advantages like wide observation area, high spatial and time resolution, and so on. In order to analyze the weather radar observation result, we should know the inside structure and data. Some non-precipitation echoes exist inside of the observed radar data. And these echoes affect decreased accuracy of weather forecasting. Therefore, this paper suggests a method that could remove line-shaped non-precipitation echo from raw radar data. The line-shaped echoes are distinguished from the raw radar data and extracted their own features. These extracted data pairs are used as learning data for naive bayesian classifier. After the learning process, the constructed naive bayesian classifier is applied to real case that includes not only line-shaped echo but also other precipitation echoes. From the experiments, we confirm that the conclusion that suggested naive bayesian classifier could distinguish line-shaped echo effectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.846-854
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• 2017

In this paper, we proposed a method to reduce the error of compass by combining the ceiling technique used in the past with modern IT technology. We combined an encoder and the Azimuth Circle for applying an algorithm. The algorithm is able to calculate the true north by using astronomical observation. Finally, we implemented the embedded system possible to indicate various situations and perform calculations. As a result, it isn't only able to calculate the true north with an error of about $0.2^{\circ}$ but also takes less than 5 seconds. Originally, using astronomical observation requires more than 5minutes. So it is analyzed as convenient by solving the problem of taking lots of time. Especially, we present the tolerance less than $0.5^{\circ}$ by the analysis of the existing gyrocompass and the bearing standard of IMO. In conclusion, we clearly confirm that the results of this paper are possible to reduce the error of various compasses in a real world.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.28 no.1
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• pp.51-61
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• 2023

Sound can travel a long distance in the ocean; hence, acoustic instruments have been widely used for ocean observations in various fields such as bathymetric survey, object detection, underwater communication, and current measurements. Herein we introduce a pressure-recording inverted echo sounder (PIES) which is one of the most powerful instruments, moored at seafloor for ocean observation in physical oceanography. The PIES can measure various kinds of oceanic phenomena (currents, mesoscale eddies, internal waves, and sea surface height variabilities) and support acoustic telemetry and pop-up data shuttle (PDS) system for remote data acquisition. In this paper, we review uses of PIES and describe present and prospective system of PIES including remote data acquisition toward (quasi) real-time data recovery.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.761-768
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• 2023

In the 4th Industrial Revolution, AI(Artificial Intelligence) and IoT(Internet of Things) technologies are being applied to across various fields, with particularly prominence in asset management, disaster management, and meteorological observation. In these fields, it is necessary to accurately determine the real-time and precise tracking of the object's location and status, and to collect various data even in situations that are difficult to detect with existing sensors. In order to address these demands, the use of GNSS(Global Navigation Satellite System) is essential, and this technology enables the efficient management of assets, disaster prevent and response, and accurate weather forecasting. In this paper, we provide the investigated results for the latest trends in the application of GNSS in the fields of asset management, disaster management, and weather observation, among various fields incorporating AI and IoT and analyze them.

• Journal of Astronomy and Space Sciences
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• v.28 no.1
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• pp.63-70
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• 2011

The needs for satellite formation flying are gradually increasing to perform the advanced space missions in remote sensing and observation of the space or Earth. Formation flying in low Earth orbit can perform the scientific missions that cannot be realized with a single spacecraft. One of the various techniques of satellite formation flying is the determination of the precise baselines between the satellites within the formation, which has to be in company with the precision validation. In this paper, the baseline of Gravity Recovery and Climate Experiment (GRACE) A and B was determined with the real global positioning system (GPS) measurements of GRACE satellites. And baseline precision was validated with the batch and sequential processing methods using K/Ka-band ranging system (KBR) biased range measurements. Because the proposed sequential method validate the baseline precision, removing the KBR bias with the epoch difference instead of its estimation, the validating data (KBR biased range) are independent of the data validated (GPS-baseline) and this method can be applied to the real-time precision validation. The result of sequential precision validation was 1.5~3.0 mm which is similar to the batch precision validation.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.119-124
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• 2009

In this paper, we propose a novel approach to estimating the real-time moving trajectory of an object is proposed in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the input-output relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.101-106
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• 2010

We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• Korean Journal of Human Ecology
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• v.17 no.3
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• pp.399-411
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• 2008

The study purposes to survey teacher's and child's difficulties which full day classes of public kindergarten regrouped in the afternoon time are having. The subjects are 4 full day class pre-service kindergarten teachers and 8 full-day class children in G Metropolitan City and in J Province. Data were collected through in depth interviews and participatory observation. According to the results, the variables of teachers' difficulties in managing full day classes regrouped in the afternoon time are "living as an outsider without a sense of belonging", "living as a false teacher rather than a real class teacher", and "living as a teacher giving specialty and aptitude education". The variables of children's difficulties are "moving like a migratory bird", "watching the clock and the door", and "being unable to concentrate". The study is expected to be useful as one of basic findings for desirable management of kindergarten full day classes regrouped in the afternoon time.