• The Bulletin of The Korean Astronomical Society
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• v.32 no.1
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• pp.105.2-105.2
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• 2007

• Current Industrial and Technological Trends in Aerospace
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• v.7 no.1
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• pp.119-127
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• 2009

There have been about 450 atomic frequency standards (or atomic clocks) launched into orbit for the use on communications and scientific payloads since 1970's. GPS satellites carry on-board Rubidium and Cesium atomic frequency standards which are utilized for the precise positioning and timing. The evolving technologies of space qualified atomic frequency standards have enhanced in the performance, reliability, and lifetime of satellites. In this paper we describe the fundamentals and performance of the atomic frequency standards, and introduce the atomic frequency standards which are presently on-board various satellites systems. We also present the GPS time scale and its applications.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.201-206
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• 2010

A project for construction of Korea Geodetic VLBI has officially started in Oct. 2008. The construction of all system will be completed by the end of 2011. The project was named Korea VLBI system for Geodesy (KVG), and its main purpose is to maintain the Korea Geodetic Datum. In case of the KVG system, an observation room where an H-maser frequency standard is located is in a building separated from an antenna by several tens of meters. Therefore KVG system will adopt a so-called round-trip system to transmit reference signals to the antenna with diminishing the effect of path length variations. KVG's round-trip system is designed not only available to use either metal or optical fiber cables, but also available to measure path length variations directly by using K5/VSSP32 sampler. We will present principle of round-trip system and the new type of round trip system for KVG.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.1
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• pp.111-115
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• 2024

This study builds a machine learning model optimized for clocks among various techniques in the field of artificial intelligence and applies it to clock stabilization or synchronization technology based on atomic clock noise characteristics. In addition, the possibility of providing stable source clock data is confirmed through the characteristics of machine learning predicted values during holdover of atomic clocks. The proposed machine learning model is evaluated by comparing its performance with the AutoRegressive Integrated Moving Average (ARIMA) model, an existing statistical clock prediction model. From the results of the analysis, the prediction model proposed in this study (MSE: 9.47476) has a lower MSE value than the ARIMA model (MSE: 221.2622), which means that it provides more accurate predictions. The prediction accuracy is based on understanding the complex nature of data that changes over time and how well the model reflects this. The application of a machine learning prediction model can be seen as a way to overcome the limitations of the statistical-based ARIMA model in time series prediction and achieve improved prediction performance.