4 research outputs found

    Comparison of Ultra-Rapid Orbit Prediction Strategies for GPS, GLONASS, Galileo and BeiDou

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    Currently, ultra-rapid orbits play an important role in the high-speed development of global navigation satellite system (GNSS) real-time applications. This contribution focuses on the impact of the fitting arc length of observed orbits and solar radiation pressure (SRP) on the orbit prediction performance for GPS, GLONASS, Galileo and BeiDou. One full yearโ€™s precise ephemerides during 2015 were used as fitted observed orbits and then as references to be compared with predicted orbits, together with known earth rotation parameters. The full nine-parameter Empirical Center for Orbit Determination in Europe (CODE) Orbit Model (ECOM) and its reduced version were chosen in our study. The arc lengths of observed fitted orbits that showed the smallest weighted root mean squares (WRMSs) and medians of the orbit differences after a Helmert transformation fell between 40 and 45 h for GPS and GLONASS and between 42 and 48 h for Galileo, while the WRMS values and medians become flat after a 42 h arc length for BeiDou. The stability of the Helmert transformation and SRP parameters also confirmed the similar optimal arc lengths. The range around 42โ€“45 h is suggested to be the optimal arc length interval of the fitted observed orbits for the multi-GNSS joint solution of ultra-rapid orbits

    Comparison of Ultra-Rapid Orbit Prediction Strategies for GPS, GLONASS, Galileo and BeiDou

    No full text
    Currently, ultra-rapid orbits play an important role in the high-speed development of global navigation satellite system (GNSS) real-time applications. This contribution focuses on the impact of the fitting arc length of observed orbits and solar radiation pressure (SRP) on the orbit prediction performance for GPS, GLONASS, Galileo and BeiDou. One full yearโ€™s precise ephemerides during 2015 were used as fitted observed orbits and then as references to be compared with predicted orbits, together with known earth rotation parameters. The full nine-parameter Empirical Center for Orbit Determination in Europe (CODE) Orbit Model (ECOM) and its reduced version were chosen in our study. The arc lengths of observed fitted orbits that showed the smallest weighted root mean squares (WRMSs) and medians of the orbit differences after a Helmert transformation fell between 40 and 45 h for GPS and GLONASS and between 42 and 48 h for Galileo, while the WRMS values and medians become flat after a 42 h arc length for BeiDou. The stability of the Helmert transformation and SRP parameters also confirmed the similar optimal arc lengths. The range around 42โ€“45 h is suggested to be the optimal arc length interval of the fitted observed orbits for the multi-GNSS joint solution of ultra-rapid orbits

    A Study on Real-time GPS Precise Orbit Determination System and Message Design of GPS Precise Orbit Covariance

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€,2020. 2. ๊ธฐ์ฐฝ๋ˆ.This study developed a centimeter-level real-time GPS precise orbit determination system for precise navigation and proposed an efficient message design of providing covariance. Global navigation satellite system is a typical navigation system that utilizes a number of satellites to provide the user's location and time. User performs navigation using satellite position and satellite time information. The orbit and clock error of a satellite contains meter-level errors and affects the user's position. Therefore, real-time precise orbit information of a centimeter-level is essential for real-time precise navigation applications such as drones, autonomous vehicles, and artificial intelligence vehicles. In addition, since the covariance of real-time precision orbit can be utilized to improve the user's position accuracy, fault detection, and calculate the level of position error, a system is needed to estimate the precise orbit and covariance. A real-time orbit determination system can estimate covariance of precise orbits using orbit dynamics and globally distributed network observations. The existing real-time orbit determination estimates the orbit error and clock error of the satellite together, but in this study, double differential measurements are used to estimate the orbit information separated from the clock error. This provides information in orbit alone, allowing relative navigation users to use it. Also, in addition to Earth's gravity, solar and lunar gravity, solar radiation pressure, gravitational field variation by tidal effect, and general relativity effects are analyzed and considered precisely. Most perturbations are well modeled, but in the case of solar radiation, estimates should be made in real-time as an environmentally sensitive component. To this end, the effects by earth and moon shadows were analyzed, and orbit determination taking into account the effects of the moon's shadow. The performance of a developed real-time precise orbit determination system was verified with IGS final orbit. 3D error and radius direction error are RMS 8cm and 2cm, respectively. Using this, the user expects to be able to improve navigation performance by utilizing precise orbits and to use covariance information to calculate the user's positional error level. Furthermore, it proposed an efficient way to provide covariance estimated in real-time GPS precision orbital determination system. Covariance of precise orbit information is highly utilized such as monitoring integrity and improving user location performance. However, since no product is currently providing orbit full covariance information, the covariance is estimated using the real-time precise orbit determination system established in this study and the provision method is proposed. The estimated covariance analyzed the interaxial correlation in the various coordinate systems, suggesting a coordinate system to ignore the interaxial correlation. The proposed measure could reduce the number of messages by 33 %, rather than providing the entire covariance information. The proposed covariance provision was evaluated at orbit confidence level in measurement and user confidence level in position error. Users' confidence level has been reduced to 30% since the satellite orbit's confidence level using covariance provides up to 55% more information than previously. As such, it is expected that the provision of covariance will improve the availability of precision navigation systems by reducing user confidence In this paper, it is expected that not only the real-time precise orbit determination system will be secured, but the system verification using actual data will be carried out so that it can be utilized in the real-time orbit determination system of the future Korean-type satellite navigation system. In addition, the proposed covariance provision could contribute to improved user location performance and integrity monitoring.์ตœ๊ทผ ์‹ค์‹œ๊ฐ„ ์‚ฌ์šฉ์ž์˜ ์ •๋ฐ€ ์œ„์น˜๋ฅผ ํ™œ์šฉํ•œ ๋“œ๋ก , ์ž์œจ์ฃผํ–‰ ์ฐจ๋Ÿ‰, ์ธ๊ณต์ง€๋Šฅ ์ž๋™์ฐจ ๋“ฑ์˜ ์–ดํ”Œ๋ฆฌ์ผ€์ด์…˜์ด ์ฆ๊ฐ€ํ•จ์— ๋”ฐ๋ผ, ์‹ค์‹œ๊ฐ„ GPS ์ •๋ฐ€ ๊ถค๋„์— ๊ด€ํ•œ ๊ด€์‹ฌ์ด ๋†’์•„์ง€๊ณ  ์žˆ๋‹ค. ์‹ค์‹œ๊ฐ„ ์ •๋ฐ€๊ถค๋„๋Š” ์‹ค์‹œ๊ฐ„ ์‚ฌ์šฉ์ž์˜ ์œ„์น˜ ์ •ํ™•๋„๋ฅผ ๊ฐœ์„ ํ•  ์ˆ˜ ์žˆ๊ณ , ์ •๋ฐ€ ๊ถค๋„์˜ ๊ณต๋ถ„์‚ฐ์€ ์‚ฌ์šฉ์ž์˜ ์œ„์น˜ ์ •ํ™•๋„ ํ–ฅ์ƒ, ๊ณ ์žฅ ๊ฐ์ง€, ์œ„์น˜ ์‹ ๋ขฐ ์ˆ˜์ค€ ๊ณ„์‚ฐ ๋“ฑ์— ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์–ด ์ •๋ฐ€ ๊ถค๋„๋ฟ ์•„๋‹ˆ๋ผ ์ •๋ฐ€ ๊ถค๋„์˜ ๊ณต๋ถ„์‚ฐ์„ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ๋Š” ์‹œ์Šคํ…œ์ด ์š”๊ตฌ๋˜๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์„ผํ‹ฐ๋ฏธํ„ฐ ์ˆ˜์ค€์˜ ์ •๋ฐ€ ๊ถค๋„ ๋ฐ ๊ณต๋ถ„์‚ฐ ์ •๋ณด๋ฅผ ์ œ๊ณตํ•  ์ˆ˜ ์žˆ๋Š” ์‹ค์‹œ๊ฐ„ GPS ์ •๋ฐ€ ๊ถค๋„ ๊ฒฐ์ • ์‹œ์Šคํ…œ์„ ๊ฐœ๋ฐœํ•˜๊ณ  ํšจ์œจ์ ์ธ ๊ณต๋ถ„์‚ฐ ์ œ๊ณต ๋ฐฉ์•ˆ์„ ์ œ์•ˆํ•œ๋‹ค. ์‹ค์‹œ๊ฐ„ GPS ์ •๋ฐ€ ๊ถค๋„ ๊ฒฐ์ • ์‹œ์Šคํ…œ์€ ์ •๋ฐ€ ๊ถค๋„ ์˜ˆ์ธก ๊ธฐ์ˆ ๊ณผ ์„ญ๋™ ๋ชจ๋ธ ๋ณ€์ˆ˜ ์ถ”์ •, ์ž๋ฃŒ ์ฒ˜๋ฆฌ ํ•„ํ„ฐ ๋“ฑ์˜ ๋ณตํ•ฉ ์‹œ์Šคํ…œ์ด๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ํ™•์žฅํ˜• ์นผ๋งŒํ•„ํ„ฐ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ์‹ค์‹œ๊ฐ„ GPS ์ •๋ฐ€ ๊ถค๋„ ๊ฒฐ์ • ์‹œ์Šคํ…œ์„ ๊ตฌํ˜„ํ•˜์—ฌ, ์‹ค์‹œ๊ฐ„ ์ •๋ฐ€ ๊ถค๋„ ๋ฐ ์ •๋ฐ€ ๊ถค๋„ ๊ณต๋ถ„์‚ฐ์„ ์ถ”์ •ํ•œ๋‹ค. ๊ธฐ์กด ์‹ค์‹œ๊ฐ„ ๊ถค๋„ ๊ฒฐ์ • ์—ฐ๊ตฌ๋Š” ์œ„์„ฑ์˜ ๊ถค๋„ ์˜ค์ฐจ์™€ ์‹œ๊ณ„์˜ค์ฐจ๋ฅผ ํ•จ๊ป˜ ์ถ”์ •ํ•˜์ง€๋งŒ, ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ด์ค‘์ฐจ๋ถ„ ์ธก์ •์น˜๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๊ถค๋„ ๋‹จ๋…์˜ ์ •๋ณด๋ฅผ ์ œ๊ณตํ•œ๋‹ค. ๋˜ํ•œ, GPS ์œ„์„ฑ ํ™˜๊ฒฝ์˜ ๊ถค๋„ ์„ญ๋™๋ ฅ์ธ ํƒœ์–‘๊ณผ ๋‹ฌ์˜ ์ค‘๋ ฅ, ํƒœ์–‘ ๋ณต์‚ฌ์••, ์กฐ์„์— ์˜ํ•œ ์ค‘๋ ฅ์žฅ ๋ณ€ํ™”, ์ผ๋ฐ˜ ์ƒ๋Œ€์„ฑ ํšจ๊ณผ์˜ ํฌ๊ธฐ๋ฅผ ๋ถ„์„ํ•˜์—ฌ, ๊ถค๋„ ํ™˜๊ฒฝ์„ ๋ถ„์„ํ–ˆ๋‹ค. ์ด ๋•Œ, ์ง€๊ตฌ ๋ฐ ๋‹ฌ ๊ทธ๋ฆผ์ž ํ™˜๊ฒฝ์„ ๋ถ„์„ํ•˜์—ฌ, ๋‹ค์–‘ํ•œ ๊ถค๋„ ํ™˜๊ฒฝ์—์„œ ๊ถค๋„ ๊ฒฐ์ • ์„ฑ๋Šฅ์„ ๋ถ„์„ํ–ˆ๋‹ค. ๊ฐœ๋ฐœ๋œ ์‹ค์‹œ๊ฐ„ ์ •๋ฐ€ ๊ถค๋„ ๊ฒฐ์ • ์‹œ์Šคํ…œ์˜ ์„ฑ๋Šฅ์€ IGS ํ›„์ฒ˜๋ฆฌ ์ •๋ฐ€ ๊ถค๋„์™€ ๋น„๊ตํ•˜์—ฌ 3D ์˜ค์ฐจ๋Š” ์œ„์„ฑ ํ‰๊ท  RMS 8cm, ๋ฐ˜๊ฒฝ ๋ฐฉํ–ฅ์œผ๋กœ 2cm ์ˆ˜์ค€์œผ๋กœ ๊ฒ€์ฆํ•˜์˜€๊ณ , ์ถ”์ •๋œ ๊ถค๋„์˜ ๊ณต๋ถ„์‚ฐ ์ •๋ณด๋Š” ์˜ค์ฐจ์˜ ํ™•๋ฅ  ๋ถ„ํฌ ๋ฐ ๋ˆ„์  ํ™•๋ฅ ๋ถ„ํฌ๋ฅผ ํ™œ์šฉํ•˜์—ฌ, ์ž˜ ๋ฐ˜์˜ํ•จ์„ ํ™•์ธํ–ˆ๋‹ค. ๋” ๋‚˜์•„๊ฐ€ ์‹ค์‹œ๊ฐ„ GPS ์ •๋ฐ€ ๊ถค๋„ ๊ณต๋ถ„์‚ฐ์˜ ํŠน์ง•์„ ๋ถ„์„ํ•˜๊ณ , ํšจ์œจ์ ์ธ ๊ณต๋ถ„์‚ฐ ์ œ๊ณต ๋ฐฉ์•ˆ์„ ์ œ์•ˆํ–ˆ๋‹ค. ์‹ค์‹œ๊ฐ„ GPS ์ •๋ฐ€ ๊ถค๋„์˜ ์‹ ๋ขฐ์ˆ˜์ค€์€ ์‚ฌ์šฉ์ž ์œ„์น˜ ์•ˆ์ „์„ ์œ„ํ•œ ๋ฌด๊ฒฐ์„ฑ, ๊ฐ€์šฉ์„ฑ ๋“ฑ์˜ ๋ถ„์•ผ์—์„œ ํ™œ์šฉ๋„๊ฐ€ ๋†’๋‹ค. ํ˜„์žฌ ์ •๋ฐ€ ๊ถค๋„์˜ ์‹ ๋ขฐ์ˆ˜์ค€์€ ์ผ๋ฐ˜์ ์œผ๋กœ User range accuracy๋กœ ์ œ๊ณต๋˜๊ณ  ์žˆ์œผ๋‚˜, ์ตœ๊ทผ ๊ถค๋„ ์˜ค์ฐจ์˜ ์ „์ฒด ๊ณต๋ถ„์‚ฐ์„ ์ œ๊ณตํ•˜๋Š” ๋ฐฉ์•ˆ์ด ์ œ์•ˆ๋˜๊ณ  ์žˆ๋‹ค. ์ •๋ฐ€ ๊ถค๋„์˜ ์ „์ฒด ๊ณต๋ถ„์‚ฐ์€ ์‚ฌ์šฉ์ž ์œ„์น˜ ์„ฑ๋Šฅ ๊ฐœ์„ , ๊ณ ์žฅ ๊ฐ์ง€ ์„ฑ๋Šฅ ํ–ฅ์ƒ, ๊ฐ€์šฉ์„ฑ ์ฆ๊ฐ€ ๋“ฑ์˜ ์„ฑ๋Šฅ ํ–ฅ์ƒ์ด ์˜ˆ์ธก๋˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜, ํ˜„์žฌ๊นŒ์ง€ ์‹ค์‹œ๊ฐ„ ๊ถค๋„ ์ „์ฒด ๊ณต๋ถ„์‚ฐ์„ ์ œ๊ณตํ•˜๊ณ  ์žˆ๋Š” ์ œํ’ˆ์ด ์—†๊ณ , ํ–ฅํ›„ ์ „์ฒด ๊ณต๋ถ„์‚ฐ์„ ์ œ๊ณตํ•˜๊ธฐ ์œ„ํ•ด ๊ด€๋ จ ์—ฐ๊ตฌ๊ฐ€ ํ•„์š”ํ•œ ์ƒํ™ฉ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ๋‹ค์–‘ํ•œ ์ขŒํ‘œ๊ณ„์—์„œ ์‹ค์‹œ๊ฐ„ GPS ์ •๋ฐ€ ๊ถค๋„์˜ ์ถ•๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ถ„์„ํ•จ์œผ๋กœ์จ ์ถ•๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ๋ฌด์‹œํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฉ์•ˆ์„ ์ œ์•ˆํ–ˆ๋‹ค. ์ œ์•ˆ๋œ ๋ฐฉ์•ˆ์€ ์ „์ฒด ๊ณต๋ถ„์‚ฐ ์ •๋ณด๋ฅผ ์ œ๊ณต์„ ์œ„ํ•œ ๋ฉ”์‹œ์ง€ ๋Ÿ‰์„ 33% ๊ฐ์†Œ์‹œํ‚ฌ ์ˆ˜ ์žˆ๊ณ , ์‹œ๋ฎฌ๋ ˆ์ด์…˜์„ ํ†ตํ•ด ๊ธฐ์กด ๋ฐฉ๋ฒ• ๋Œ€๋น„ ์œ„์„ฑ ๊ถค๋„์˜ ์ธก์ •์น˜ ๋‚ด ์˜ค์ฐจ ์‹ ๋ขฐ ์ˆ˜์ค€์˜ ํฌ๊ธฐ๋Š” 55%, ์‚ฌ์šฉ์ž์˜ ์œ„์น˜ ์‹ ๋ขฐ ์ˆ˜์ค€์˜ ํฌ๊ธฐ๋Š” 30% ์ˆ˜์ค€์œผ๋กœ ๊ฐ์†Œํ•จ์„ ํ™•์ธํ–ˆ๋‹ค. ๋”ฐ๋ผ์„œ, ์ œ์•ˆ๋œ ๋ฐฉ๋ฒ•์€ ์ „์ฒด ๊ณต๋ถ„์‚ฐ ์ œ๊ณต์„ ์œ„ํ•œ ๋ฉ”์‹œ์ง€๋Ÿ‰์„ ์ค„์ด๊ณ , ์ •๋ฐ€ ํ•ญ๋ฒ• ์‹œ์Šคํ…œ์˜ ๊ฐ€์šฉ์„ฑ์„ ๊ฐœ์„ ์‹œํ‚ฌ ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์€ ์‹ค์‹œ๊ฐ„ GPS ์ •๋ฐ€ ๊ถค๋„ ๊ฒฐ์ • ์‹œ์Šคํ…œ์„ ์ •๋ฐ€ํ•˜๊ฒŒ ๊ตฌํ˜„ํ•˜์—ฌ, ๊ตญ๋‚ด ์‹ค์‹œ๊ฐ„ GPS ์ •๋ฐ€ ๊ถค๋„ ๊ฒฐ์ • ์‹œ์Šคํ…œ์˜ ์„ฑ๋Šฅ์„ ์„ผํ‹ฐ๋ฏธํ„ฐ ์ˆ˜์ค€์œผ๋กœ ํ–ฅ์ƒ์‹œ์ผฐ์œผ๋ฉฐ, ํšจ์œจ์ ์ธ ๊ถค๋„ ๊ณต๋ถ„์‚ฐ ์ œ๊ณต๋ฐฉ์•ˆ์„ ์ œ์•ˆํ–ˆ๋‹ค. ์‹ค์‹œ๊ฐ„ ๊ตฌ์กฐ์™€ ์‹ค์‹œ๊ฐ„ GPS ์ •๋ฐ€ ๊ถค๋„ ๊ฒฐ์ •์˜ ๊ธฐ๋ฐ˜ ๊ธฐ์ˆ ์€ ํ–ฅํ›„ ํ•œ๊ตญํ˜• ์œ„์„ฑํ•ญ๋ฒ• ์‹œ์Šคํ…œ์˜ ์‹ค์‹œ๊ฐ„ ๊ถค๋„ ๊ฒฐ์ •์— ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€ํ•œ๋‹ค. ๋˜ํ•œ ์ œ์•ˆ๋œ ๊ณต๋ถ„์‚ฐ ์ œ๊ณต ๋ฐฉ์•ˆ์€ GPS ๋ฟ ์•„๋‹ˆ๋ผ ๋‹ค์–‘ํ•œ ์œ„์„ฑํ•ญ๋ฒ• ์‹œ์Šคํ…œ์˜ ๊ณต๋ถ„์‚ฐ ์ œ๊ณต ํŒŒ๋ผ๋ฏธํ„ฐ๋ฅผ ํšจ์œจ์ ์œผ๋กœ ์ œ๊ณตํ•จ์œผ๋กœ์จ ์‚ฌ์šฉ์ž ์œ„์น˜ ์„ฑ๋Šฅ ํ–ฅ์ƒ ๋ฐ ๋ฌด๊ฒฐ์„ฑ ๊ฐ์‹œ ๋“ฑ์— ๊ธฐ์—ฌํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€ํ•œ๋‹ค.1์žฅ. ์„œ ๋ก  ๏ผ‘ 1. ์—ฐ๊ตฌ ๋™๊ธฐ ๋ฐ ๋ชฉ์  ๏ผ‘ 2. ์—ฐ๊ตฌ ๋™ํ–ฅ ๏ผ“ 1) ์‹ค์‹œ๊ฐ„ GPS ์ •๋ฐ€ ๊ถค๋„ ๊ฒฐ์ • ์‹œ์Šคํ…œ ๏ผ” 2) ์‹ค์‹œ๊ฐ„ ์ •๋ฐ€ ๊ถค๋„ ์‹ ๋ขฐ์ˆ˜์ค€ ์ œ๊ณต ์—ฐ๊ตฌ ๏ผ– 3. ์—ฐ๊ตฌ ๋‚ด์šฉ ๋ฐ ๋ฐฉ๋ฒ• ๏ผ— 4. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ์˜ ๊ธฐ์—ฌ๋„ ๏ผ˜ 2์žฅ. ์‹ค์‹œ๊ฐ„ GPS ์ •๋ฐ€ ๊ถค๋„ ๊ฒฐ์ •์„ ์œ„ํ•œ ๊ธฐ๋ณธ ์š”์†Œ ๏ผ‘๏ผ 1. GPS ์‹œ์Šคํ…œ ๏ผ‘๏ผ 1) GPS ์‹œ์Šคํ…œ ๊ฐœ์š” ๏ผ‘๏ผ 2) GPS ์ธก์ •์น˜ ๏ผ‘๏ผ‘ 3) GPS ์ธก์ •์น˜ ๊ธฐํƒ€ ์˜ค์ฐจ ์š”์†Œ ๏ผ‘๏ผ“ 2. IGS ๏ผ’๏ผ 3. ์‹œ๊ฐ„๊ณ„ ๋ฐ ์ขŒํ‘œ๊ณ„ ๏ผ’๏ผ’ 1) ์‹œ๊ฐ„๊ณ„ ๏ผ’๏ผ’ 2) ์ขŒํ‘œ๊ณ„ ๏ผ’๏ผ• 4. GPS ์œ„์„ฑ ๋™์—ญํ•™ ๏ผ’๏ผ— 1) ์ง€๊ตฌ์˜ ์ค‘๋ ฅ ๏ผ’๏ผ˜ 2) 3์ฒด ์ค‘๋ ฅ ๏ผ’๏ผ™ 3) ํƒœ์–‘ ๋ณต์‚ฌ์•• (Solar radiation pressure) ๏ผ“๏ผ 4) ์ง€๊ตฌ ๋ณต์‚ฌ์•• ๏ผ“๏ผ” 5) ์กฐ์„์— ์˜ํ•œ ์ค‘๋ ฅ์žฅ ๋ณ€ํ™” (Tidal effect) ๏ผ“๏ผ” 6) ์ƒ๋Œ€์„ฑ ํšจ๊ณผ ๏ผ“๏ผ– 3์žฅ. ์‹ค์‹œ๊ฐ„ GPS ์œ„์„ฑ ์ •๋ฐ€ ๊ถค๋„ ๊ฒฐ์ • ์‹œ์Šคํ…œ ๏ผ“๏ผ˜ 1. ๊ฐœ์š” ๏ผ“๏ผ˜ 2. GPS ์ธก์ •์น˜ ๊ด€์ธก ๋ชจ๋ธ ๏ผ”๏ผ” 3. EKF ํ•„ํ„ฐ ๏ผ”๏ผ– 4. ๊ถค๋„ ์ „ํŒŒ ๋ชจ๋ธ ๏ผ•๏ผ 5. ์ˆ˜์น˜ ์ ๋ถ„ ๋ชจ๋ธ ๏ผ•๏ผ’ 6. ์•Œ๊ณ ๋ฆฌ์ฆ˜ ํšจ์œจํ™” ๏ผ•๏ผ” 4์žฅ. ์‹ค์‹œ๊ฐ„ GPS ์ •๋ฐ€ ๊ถค๋„ ๊ฒฐ์ • ๊ณ„์‚ฐ ๋ฐ ๊ฒ€์ฆ ๏ผ•๏ผ• 1. GPS ๊ถค๋„ ํ™˜๊ฒฝ ๋ถ„์„ ๏ผ•๏ผ• 1) ์ง€๊ตฌ ๊ทธ๋ฆผ์ž ๏ผ•๏ผ– 2) ๋‹ฌ ๊ทธ๋ฆผ์ž ๏ผ–๏ผ 2. ์‹ค์‹œ๊ฐ„ GPS ์ •๋ฐ€ ๊ถค๋„ ๊ฒฐ์ • ์‹œ์Šคํ…œ ๊ฒ€์ฆ ๊ฒฐ๊ณผ ๏ผ–๏ผ“ 1) ๋ฐ์ดํ„ฐ ์ฒ˜๋ฆฌ ํ™˜๊ฒฝ ๏ผ–๏ผ“ 2) ์‹ค์‹œ๊ฐ„ GPS ์ •๋ฐ€ ๊ถค๋„ ๊ฒฐ์ • ์‹œ์Šคํ…œ ๊ณ„์‚ฐ ๊ฒฐ๊ณผ ๏ผ–๏ผ” 3) ๋‹ฌ ๊ทธ๋ฆผ์ž ๋ชจ๋ธ ์˜ํ–ฅ ๋ถ„์„ ๏ผ–๏ผ™ 5์žฅ. ์‹ค์‹œ๊ฐ„ ์ •๋ฐ€ ํ•ญ๋ฒ• ์‚ฌ์šฉ์ž๋ฅผ ์œ„ํ•œ ๊ณต๋ถ„์‚ฐ ์ œ๊ณต ๋ฐฉ์•ˆ ์„ค๊ณ„ ๏ผ—๏ผ— 1. ๊ถค๋„ ๊ณต๋ถ„์‚ฐ์˜ ์ถ•๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„ ๋ถ„์„ ๏ผ—๏ผ— 1) ๋‹ค์–‘ํ•œ ์ขŒํ‘œ๊ณ„์—์„œ ๊ถค๋„ ๊ณต๋ถ„์‚ฐ ๋ถ„์„ ๏ผ—๏ผ˜ 2) ์‹œ๊ฐ„์— ๋”ฐ๋ฅธ ์ถ•๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„ ๏ผ˜๏ผ“ 3) RSW์™€ RAC ์ขŒํ‘œ๊ณ„์˜ ์ถ•๊ฐ„ ์ƒ๊ด€๊ด€๊ณ„ ๏ผ˜๏ผ– 4) ํšจ์œจ์ ์ธ ์ œ๊ณต๋ฐฉ์•ˆ ์„ค๊ณ„ ๏ผ˜๏ผ˜ 5) ๊ณต๋ถ„์‚ฐ ์ œ๊ณต ๋ฐฉ๋ฒ• ๋ณ„ ๋น„๊ต ๏ผ™๏ผ’ 2. ์‹ค์‹œ๊ฐ„ ์ •๋ฐ€ ํ•ญ๋ฒ• ์‚ฌ์šฉ์ž๋ฅผ ์œ„ํ•œ ์ •๋ฐ€ ๊ถค๋„ ๊ณต๋ถ„์‚ฐ ์ œ๊ณต ๋ฐฉ์•ˆ ๋ฐ ํšจ๊ณผ ๏ผ™๏ผ— 1) ์‚ฌ์šฉ์ž ์œ„์น˜ ์‹ ๋ขฐ ์ˆ˜์ค€๊ณผ ๊ถค๋„ ์˜ค์ฐจ ์‹ ๋ขฐ์ˆ˜์ค€ ๏ผ™๏ผ— 2) ๊ถค๋„ ์‹ ๋ขฐ ์ˆ˜์ค€ ์ œ๊ณต ๋ฐฉ๋ฒ•์˜ ์ข…๋ฅ˜ ๏ผ‘๏ผ๏ผ‘ 3) ์œ„์น˜์— ๋”ฐ๋ฅธ ๊ถค๋„ ์‹ ๋ขฐ์ˆ˜์ค€ ๋ถ„์„ ๏ผ‘๏ผ๏ผ“ 4) ์œ„์น˜์— ๋”ฐ๋ฅธ ์‚ฌ์šฉ์ž ์œ„์น˜ ์‹ ๋ขฐ์ˆ˜์ค€ ๋ถ„์„ ๏ผ‘๏ผ๏ผ™ 6์žฅ. ๊ฒฐ๋ก  ๋ฐ ํ–ฅํ›„ ๊ณผ์ œ ๏ผ‘๏ผ‘๏ผ’ 1. ๊ฒฐ๋ก  ๏ผ‘๏ผ‘๏ผ’ 2. ํ–ฅํ›„ ๊ณผ์ œ ๏ผ‘๏ผ‘๏ผ“ ์ฐธ๊ณ  ๋ฌธํ—Œ ๏ผ‘๏ผ‘๏ผ—Docto

    ์„ผํ‹ฐ๋ฏธํ„ฐ ๊ธ‰ ๊ด‘์—ญ ๋ณด๊ฐ•ํ•ญ๋ฒ• ์‹œ์Šคํ…œ์˜ ๋ฐ˜์†กํŒŒ ์œ„์ƒ ๊ธฐ๋ฐ˜ ๋ณด์ •์ •๋ณด ์ƒ์„ฑ ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€,2020. 2. ๊ธฐ์ฐฝ๋ˆ.Recently, the demand for high-precision navigation systems for centimeter-level service has been growing rapidly for various Global Navigation Satellite System (GNSS) applications. The network Real-Time Kinematic (RTK) is one of the candidate solution to provide high-accuracy position to user in real-time. However, the network RTK requires a lot of reference stations for nationwide service. Furthermore, it requires high-speed data-link for broadcasting their scalar-type corrections. This dissertation proposed a new concept of satellite augmentation system called Compact Wide-Area RTK, which provides centimeter-level positioning service on national or continental scales to overcoming the limitation of the legacy network RTK methods. Using the wide-area network of multiple reference stations whose distance is 200~1,000 km, the proposed system generates three types of carrier-phase-based corrections: satellite orbit corrections, satellite code/phase clock (CPC) corrections, tropospheric corrections. Through the strategy of separating the scalar-type corrections of network RTK into vector forms of each error component, it is enable to expand network RTK coverage to continental scale using a similar number of reference stations as legacy meter-level Satellite-Based Augmentation System (SBAS). Furthermore, it is possible to broadcast their corrections over a wide-area using geosynchronous (GEO) satellite with extremely low-speed datalink of 250 bps likewise of legacy SBAS. To sum up, the proposed system can improve position accuracy by centimeter-level while maintaining the hardware infrastructure of the meter-level legacy SBAS. This study mainly discussed on the overall system architecture and core algorithms for generating satellite CPC corrections and tropospheric corrections. This study proposed a new Three-Carrier Ambiguity Resolution (TCAR) algorithm using ionosphere-free combinations to correctly solve the integer ambiguity in wide-area without any ionospheric corrections. The satellite CPC corrections are calculated based on multiple stations for superior and robust performance under communication delay and outage. The proposed algorithm dramatically reduced the latency compensation errors and message amounts with compare to conventional RTK protocols. The tropospheric corrections of the compact wide-area RTK system are computed using GPS-estimated precise tropospheric delay and weather data based model together. The proposed algorithm adopts spherical harmonics function to significantly reduce the message amounts and required number of GPS reference stations than the network RTK and Precise Point Positioning-RTK (PPP-RTK), while accurately modeling the spatial characteristic of tropospheric delay with weather data together. In order to evaluate the user domain performance of the compact wide-area RTK system, this study conducted the feasibility test on mid-west and south USA using actual GPS measurements. As a result, the 95% horizontal position error is about 1.9 cm and the 95% vertical position error is 7.0 cm after the integer ambiguity is correctly fixed using GPS-only signals. The user ambiguity resolution takes about 2 minutes, and success-fix rate is about 100 % when stable tropospheric condition. In conclusion, the compact wide-area RTK system can provide centimeter-level positioning service to wide-area coverage with extremely low-speed data link via GEO satellite. We hope that this new system will consider as candidate solution for nationwide centimeter-level service such as satellite augmentation system of the Korea Positioning System (KPS).์ตœ๊ทผ ์ž์œจ์ฃผํ–‰์ž๋™์ฐจ, ๋ฌด์ธ ๋“œ๋ก  ๋ฐฐ์†ก, ์ถฉ๋Œ ํšŒํ”ผ, ๋ฌด์ธํŠธ๋ž™ํ„ฐ๋ฅผ ์ด์šฉํ•œ ์Šค๋งˆํŠธ ๋ฌด์ธ ๊ฒฝ์ž‘ ๋“ฑ ์œ„์„ฑํ•ญ๋ฒ•์‹œ์Šคํ…œ(GNSS, Global Navigation Satellite System)์„ ์‚ฌ์šฉํ•˜๋Š” ๋‹ค์–‘ํ•œ ์‘์šฉ๋ถ„์•ผ์—์„œ ์ˆ˜ cm ์ˆ˜์ค€์˜ ์ •๋ฐ€ ์œ„์น˜ ์ •๋ณด์— ๋Œ€ํ•œ ์š”๊ตฌ๊ฐ€ ๊ธ‰๊ฒฉํžˆ ์ฆ๊ฐ€ํ•˜๊ณ  ์žˆ๋‹ค. ๋ณธ ํ•™์œ„๋…ผ๋ฌธ์—์„œ๋Š” 1 m ๊ธ‰์˜ ์ •ํ™•ํ•˜๊ณ  ์‹ ๋ขฐ์„ฑ ๋†’์€ ์œ„์น˜ ์„œ๋น„์Šค๋ฅผ ์ œ๊ณตํ•˜๋Š” ๊ธฐ์กด์˜ ์ •์ง€๊ถค๋„์œ„์„ฑ ๊ธฐ๋ฐ˜ ๊ด‘์—ญ ๋ณด๊ฐ•ํ•ญ๋ฒ• ์‹œ์Šคํ…œ(SBAS, Satellite-Based Augmentation System)์˜ ๊ธฐ์ค€๊ตญ ์ธํ”„๋ผ๋ฅผ ์œ ์ง€ํ•˜๋ฉด์„œ ํ•ญ๋ฒ• ์„ฑ๋Šฅ์„ ์ˆ˜ cm ์ˆ˜์ค€์œผ๋กœ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์œ„ํ•ด ๋ฐ˜์†กํŒŒ ์œ„์ƒ ๊ธฐ๋ฐ˜์˜ ์ดˆ์ •๋ฐ€ ๋ณด์ •์ •๋ณด ์ƒ์„ฑ ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ๊ด€ํ•œ ์—ฐ๊ตฌ๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์‹ค์‹œ๊ฐ„ ์ •๋ฐ€ ์ธก์œ„(RTK, Real-Time Kinematic)๋Š” ๋ฐ˜์†กํŒŒ ์œ„์ƒ ์ธก์ •์น˜์— ํฌํ•จ๋œ ๋ฏธ์ง€์ •์ˆ˜๋ฅผ ์ •ํ™•ํ•˜๊ฒŒ ๊ฒฐ์ •ํ•˜์—ฌ ์ˆ˜ cm ์ˆ˜์ค€์˜ ์ •๋ฐ€ ํ•ญ๋ฒ• ์„œ๋น„์Šค๋ฅผ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜๋Š” ๋Œ€ํ‘œ์ ์ธ ๊ธฐ๋ฒ•์ด๋‹ค. ๊ทธ ์ค‘์—์„œ๋„ ์•ฝ 50~70 km ๊ฐ„๊ฒฉ์œผ๋กœ ๋ถ„ํฌ๋œ ๋‹ค์ˆ˜์˜ ๊ธฐ์ค€๊ตญ ์ •๋ณด๋ฅผ ํ™œ์šฉํ•˜๋Š” Network RTK ๊ธฐ๋ฒ•์€ ๋™์  ์‚ฌ์šฉ์ž์˜ ๋น ๋ฅด๊ณ  ์ •ํ™•ํ•œ ์œ„์น˜ ๊ฒฐ์ •์ด ๊ฐ€๋Šฅํ•œ ์ธํ”„๋ผ๋กœ์„œ ์ฃผ๋ชฉ๋ฐ›๊ณ  ์žˆ๋‹ค. ํ•˜์ง€๋งŒ ์Šค์นผ๋ผ ํ˜•ํƒœ๋กœ ๊ตฌ์„ฑ๋œ Network RTK ๋ณด์ •์ •๋ณด๋Š” ๊ฐ ๊ธฐ์ค€๊ตญ ๋ณ„๋กœ ๊ด€์ธก๋œ ์œ„์„ฑ ์ˆ˜์— ๋”ฐ๋ผ ์ƒ์„ฑ์ด ๋˜๊ธฐ ๋•Œ๋ฌธ์— ๋ณด์ • ๋ฐ์ดํ„ฐ ๋Ÿ‰์ด ์ƒ๋‹นํžˆ ๋ฐฉ๋Œ€ํ•˜๋‹ค. ๋ฉ”์‹œ์ง€ ์ „์†ก์— ํ•„์š”ํ•œ ๋ฐ์ดํ„ฐ ๋Ÿ‰์ด ๋งŽ์„์ˆ˜๋ก ๊ณ ์†์˜ ํ†ต์‹  ํ™˜๊ฒฝ์„ ํ•„์š”๋กœ ํ•˜๋ฉฐ, ๋ฉ”์‹œ์ง€ ์‹œ๊ฐ„ ์ง€์—ฐ์ด๋‚˜ ํ†ต์‹  ๋‹จ์ ˆ์— ๋งค์šฐ ์ทจ์•ฝํ•œ ๋ฌธ์ œ๋ฅผ ๊ฐ€์ง€๊ณ  ์žˆ๋‹ค. ๋˜ํ•œ ์Šค์นผ๋ผ ํ˜•ํƒœ์˜ ๋ณด์ •์ •๋ณด๋Š” ์‚ฌ์šฉ์ž์™€ ๊ธฐ์ค€๊ตญ ๊ฐ„์˜ ๊ฑฐ๋ฆฌ๊ฐ€ ๋ฉ€์–ด์งˆ์ˆ˜๋ก ๋ณด์ • ์˜ค์ฐจ๊ฐ€ ํฌ๊ฒŒ ๋ฐœ์ƒํ•˜๊ธฐ ๋•Œ๋ฌธ์— ๋Œ€๋ฅ™ ํ˜น์€ ๋‚˜๋ผ ๊ทœ๋ชจ์˜ ๊ด‘์—ญ์—์„œ ์„œ๋น„์Šคํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ์ˆ˜์‹ญ~์ˆ˜๋ฐฑ ๊ฐœ ์ด์ƒ์˜ ๊ธฐ์ค€๊ตญ ์ธํ”„๋ผ ๊ตฌ์ถ•์ด ํ•„์ˆ˜์ ์ด๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, SBAS๊ฐ€ ํ•œ๋ฐ˜๋„ ์ง€์—ญ ์„œ๋น„์Šค๋ฅผ ์œ„ํ•ด 5~7๊ฐœ์˜ ๊ธฐ์ค€๊ตญ์ด ํ•„์š”ํ•œ ๋ฐ˜๋ฉด Network RTK๋Š” 90~100๊ฐœ์˜ ๊ธฐ์ค€๊ตญ์ด ํ•„์š”ํ•˜๋‹ค. ์ฆ‰ Network RTK๋Š” ์‹œ์Šคํ…œ ๊ตฌ์ถ• ๋ฐ ์œ ์ง€ ๋น„์šฉ์ด SBAS ๋Œ€๋น„ ์•ฝ 15๋ฐฐ ์ •๋„ ๋งŽ์ด ๋“ค๊ฒŒ ๋œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๊ธฐ์กด Network RTK์˜ ๋ฌธ์ œ์ ์„ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•œ ๋ฐฉ๋ฒ•์œผ๋กœ ๋Œ€๋ฅ™ ๊ธ‰ ๊ด‘๋ฒ”์œ„ํ•œ ์˜์—ญ์—์„œ ์‹ค์‹œ๊ฐ„์œผ๋กœ cm๊ธ‰ ์ดˆ์ •๋ฐ€ ์œ„์น˜๊ฒฐ์ • ์„œ๋น„์Šค ์ œ๊ณต์ด ๊ฐ€๋Šฅํ•œ Compact Wide-Area RTK ๋ผ๋Š” ์ƒˆ๋กœ์šด ๊ฐœ๋…์˜ ๊ด‘์—ญ๋ณด๊ฐ•ํ•ญ๋ฒ•์‹œ์Šคํ…œ ์•„ํ‚คํ…์ฒ˜๋ฅผ ์ œ์•ˆํ•˜์˜€๋‹ค. Compact Wide-Area RTK๋Š” ์•ฝ 200~1,000 km ๊ฐ„๊ฒฉ์œผ๋กœ ๋„“๊ฒŒ ๋ถ„ํฌ๋œ ๊ธฐ์ค€๊ตญ ๋„คํŠธ์›Œํฌ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๋ฐ˜์†กํŒŒ ์œ„์ƒ ๊ธฐ๋ฐ˜์˜ ์ •๋ฐ€ํ•œ ์œ„์„ฑ ๊ถค๋„ ๋ณด์ •์ •๋ณด, ์œ„์„ฑ Code/Phase ์‹œ๊ณ„ ๋ณด์ •์ •๋ณด, ๋Œ€๋ฅ˜์ธต ๋ณด์ •์ •๋ณด๋ฅผ ์ƒ์„ฑํ•˜๋Š” ์‹œ์Šคํ…œ์ด๋‹ค. ๊ธฐ์กด ์Šค์นผ๋ผ ํ˜•ํƒœ์˜ Network RTK ๋ณด์ •์ •๋ณด ๋Œ€์‹  ์˜ค์ฐจ ์š”์†Œ ๋ณ„ ๋ฒกํ„ฐ ํ˜•ํƒœ์˜ ์ •๋ฐ€ ๋ณด์ •์ •๋ณด๋ฅผ ์ƒ์„ฑํ•จ์œผ๋กœ์จ ๋ฐ์ดํ„ฐ ๋Ÿ‰์„ ํš๊ธฐ์ ์œผ๋กœ ์ ˆ๊ฐํ•˜๊ณ  ์„œ๋น„์Šค ์˜์—ญ์„ ํ™•์žฅํ•  ์ˆ˜ ์žˆ๋‹ค. ์ตœ์ข…์ ์œผ๋กœ SBAS์™€ ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ 250 bps์˜ ์ €์† ํ†ต์‹  ๋งํฌ๋ฅผ ๊ฐ€์ง„ ์ •์ง€๊ถค๋„์œ„์„ฑ์„ ํ†ตํ•ด ๊ด‘์—ญ์œผ๋กœ ๋ณด์ •์ •๋ณด ๋ฐฉ์†ก์ด ๊ฐ€๋Šฅํ•˜๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” 3๊ฐ€์ง€ ๋ณด์ •์ •๋ณด ์ค‘ ์œ„์„ฑ Code/Phase ์‹œ๊ณ„ ๋ณด์ •์ •๋ณด์™€ ๋Œ€๋ฅ˜์ธต ๋ณด์ •์ •๋ณด ์ƒ์„ฑ์„ ์œ„ํ•œ ํ•ต์‹ฌ ์•Œ๊ณ ๋ฆฌ์ฆ˜์— ๋Œ€ํ•ด ์ค‘์ ์ ์œผ๋กœ ์—ฐ๊ตฌํ•˜์˜€๋‹ค. ๋ฐ˜์†กํŒŒ ์œ„์ƒ ๊ธฐ๋ฐ˜์˜ ์ •๋ฐ€ ๋ณด์ •์ •๋ณด ์ƒ์„ฑ์„ ์œ„ํ•ด์„œ๋Š” ๋จผ์ € ๋ฏธ์ง€์ •์ˆ˜๋ฅผ ์ •ํ™•ํ•˜๊ฒŒ ๊ฒฐ์ •ํ•ด์•ผ ํ•œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์‚ผ์ค‘ ์ฃผํŒŒ์ˆ˜ ๋ฐ˜์†กํŒŒ ์œ„์ƒ ์ธก์ •์น˜์˜ ๋ฌด-์ „๋ฆฌ์ธต ์กฐํ•ฉ์„ ํ™œ์šฉํ•˜์—ฌ ์ „๋ฆฌ์ธต ๋ณด์ •์ •๋ณด ์—†์ด๋„ ์ •ํ™•ํ•˜๊ฒŒ ๋ฏธ์ง€์ •์ˆ˜ ๊ฒฐ์ • ๊ฐ€๋Šฅํ•œ ์ƒˆ๋กœ์šด ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ์œ„์„ฑ Code/Phase ์‹œ๊ณ„ ๋ณด์ •์ •๋ณด๋Š” ํ†ต์‹  ์ง€์—ฐ ๋ฐ ๊ณ ์žฅ ์‹œ ์šฐ์ˆ˜ํ•˜๊ณ  ๊ฐ•๊ฑดํ•œ ์„ฑ๋Šฅ์„ ์œ„ํ•ด ๋‹ค์ค‘ ๊ธฐ์ค€๊ตญ์˜ ๋ชจ๋“  ์ธก์ •์น˜๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์ถ”์ •๋œ๋‹ค. ์ด ๋•Œ ๊ฐ ๊ธฐ์ค€๊ตญ ๋ณ„ ์„œ๋กœ ๋‹ค๋ฅธ ๋ฏธ์ง€์ •์ˆ˜ ๋•Œ๋ฌธ์— ๋ฐœ์ƒํ•˜๋Š” ๋ฌธ์ œ๋Š” ์•ž์„œ ์ •ํ™•ํ•˜๊ฒŒ ๊ฒฐ์ •๋œ ๊ธฐ์ค€๊ตญ ๊ฐ„ ์ด์ค‘์ฐจ๋ถ„ ๋œ ๋ฏธ์ง€์ •์ˆ˜๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์ˆ˜์ค€์„ ์กฐ์ •ํ•˜๋Š” ๊ณผ์ •์„ ํ†ตํ•ด ํ•ด๊ฒฐ์ด ๊ฐ€๋Šฅํ•˜๋‹ค. ๊ทธ ๊ฒฐ๊ณผ ์ƒ์„ฑ๋œ ์œ„์„ฑ Code/Phase ๋ณด์ •์ •๋ณด ๋ฉ”์‹œ์ง€์˜ ํฌ๊ธฐ, ๋ณ€ํ™”์œจ, ์žก์Œ ์ˆ˜์ค€์ด ํฌ๊ฒŒ ๊ฐœ์„ ๋˜์—ˆ๊ณ , ํ†ต์‹  ์ง€์—ฐ ์‹œ ์˜ค์ฐจ ๋ณด์ƒ ์„ฑ๋Šฅ์ด ๊ธฐ์กด RTK ํ”„๋กœํ† ์ฝœ ๋ณด๋‹ค 99% ํ–ฅ์ƒ ๋จ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋Œ€๋ฅ˜์ธต ๋ณด์ •์ •๋ณด๋Š” ์ ์€ ์ˆ˜์˜ ๊ธฐ์ค€๊ตญ ๋งŒ์„ ํ™œ์šฉํ•˜์—ฌ ์ •ํ™•ํ•˜๊ฒŒ ๋Œ€๋ฅ˜์ธต์„ ๋ชจ๋ธ๋งํ•˜๊ธฐ ์œ„ํ•ด ์ž๋™ ๊ธฐ์ƒ๊ด€์ธก์‹œ์Šคํ…œ์œผ๋กœ๋ถ€ํ„ฐ ์ˆ˜์ง‘ํ•œ ๊ธฐ์ƒ ์ •๋ณด๋ฅผ ์ถ”๊ฐ€๋กœ ํ™œ์šฉํ•˜์—ฌ ์ƒ์„ฑ๋œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” GNSS ๊ธฐ์ค€๊ตญ ๋„คํŠธ์›Œํฌ๋กœ๋ถ€ํ„ฐ ์ •๋ฐ€ํ•˜๊ฒŒ ์ถ”์ •๋œ ๋ฐ˜์†กํŒŒ ์œ„์ƒ ๊ธฐ๋ฐ˜ ์ˆ˜์ง ๋Œ€๋ฅ˜์ธต ์ง€์—ฐ๊ณผ ๊ธฐ์ƒ์ •๋ณด ๊ธฐ๋ฐ˜์œผ๋กœ ๋ชจ๋ธ๋ง ๋œ ์ˆ˜์ง ๋Œ€๋ฅ˜์ธต ์ง€์—ฐ์„ ํ•จ๊ป˜ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ์ƒˆ๋กœ์šด ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ œ์•ˆํ•˜์˜€๋‹ค. ๊ตฌ๋ฉด์กฐํ™”ํ•จ์ˆ˜๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ Network RTK ๋ฐ PPP-RTK ๋ณด๋‹ค ํ•„์š”ํ•œ ๋ฉ”์‹œ์ง€ ์–‘๊ณผ ๊ธฐ์ค€๊ตญ ์ˆ˜๋ฅผ ํฌ๊ฒŒ ๊ฐ์†Œ์‹œํ‚ค๋ฉด์„œ๋„ RMS 2 cm ์ˆ˜์ค€์œผ๋กœ ์ •ํ™•ํ•œ ๋ณด์ •์ •๋ณด ์ƒ์„ฑ์ด ๊ฐ€๋Šฅํ•จ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ ์ œ์•ˆํ•œ Compact Wide-Area RTK ์‹œ์Šคํ…œ์˜ ํ•ญ๋ฒ• ์„ฑ๋Šฅ์„ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด ๋ฏธ๊ตญ ๋™๋ถ€ ์ง€์—ญ 6๊ฐœ ๊ธฐ์ค€๊ตญ์˜ ์‹ค์ธก GPS ๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ํ…Œ์ŠคํŠธ๋ฅผ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ ์ œ์•ˆํ•œ ์‹œ์Šคํ…œ์€ ๋ฏธ์ง€์ •์ˆ˜ ๊ฒฐ์ • ์ดํ›„ ์‚ฌ์šฉ์ž์˜ 95% ์ˆ˜ํ‰ ์œ„์น˜ ์˜ค์ฐจ 1.9 cm, 95% ์ˆ˜์ง ์œ„์น˜ ์˜ค์ฐจ 7.0 cm ๋กœ ์œ„์น˜๋ฅผ ์ •ํ™•ํ•˜๊ฒŒ ๊ฒฐ์ •ํ•˜์˜€๋‹ค. ์‚ฌ์šฉ์ž ๋ฏธ์ง€์ •์ˆ˜ ๊ฒฐ์ • ์„ฑ๋Šฅ์€ ๋Œ€๋ฅ˜์ธต ์•ˆ์ • ์ƒํƒœ์—์„œ ์•ฝ 2๋ถ„ ๋‚ด๋กœ 100% ์˜ ์„ฑ๊ณต๋ฅ ์„ ๊ฐ€์ง„๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ ์ œ์•ˆํ•œ ์‹œ์Šคํ…œ์ด ํ–ฅํ›„ ํ•œ๊ตญํ˜• ์œ„์„ฑํ•ญ๋ฒ• ์‹œ์Šคํ…œ(KPS, Korean Positioning System)์˜ ์ „๊ตญ ๋‹จ์œ„ ์„ผํ‹ฐ๋ฏธํ„ฐ ๊ธ‰ ์„œ๋น„์Šค๋ฅผ ์œ„ํ•œ ์•Œ๊ณ ๋ฆฌ์ฆ˜์œผ๋กœ ํ™œ์šฉ๋˜๊ธฐ๋ฅผ ๊ธฐ๋Œ€ํ•œ๋‹ค.CHAPTER 1. Introduction 1 1.1 Motivation and Purpose 1 1.2 Former Research 4 1.3 Outline of the Dissertation 7 1.4 Contributions 8 CHAPTER 2. Overview of GNSS Augmentation System 11 2.1 GNSS Measurements 11 2.2 GNSS Error Sources 14 2.2.1 Traditional GNSS Error Sources 14 2.2.2 Special GNSS Error Sources 21 2.2.3 Summary 28 2.3 GNSS Augmentation System 29 2.3.1 Satellite-Based Augmentation System (SBAS) 29 2.3.2 Real-Time Kinematic (RTK) 32 2.3.3 Precise Point Positioning (PPP) 36 2.3.4 Summary 40 CHAPTER 3. Compact Wide-Area RTK System Architecture 43 3.1 Compact Wide-Area RTK Architecture 43 3.1.1 WARTK Reference Station (WRS) 48 3.1.2 WARTK Processing Facility (WPF) 51 3.1.3 WARTK User 58 3.2 Ambiguity Resolution and Validation Algorithms of Compact Wide-Area RTK System 59 3.2.1 Basic Theory of Ambiguity Resolution and Validation 60 3.2.2 A New Ambiguity Resolution Algorithms for Multi-Frequency Signals 65 3.2.3 Extra-Wide-Lane (EWL) Ambiguity Resolution 69 3.2.4 Wide-Lane (WL) Ambiguity Resolution 71 3.2.5 Narrow-Lane (NL) Ambiguity Resolution 78 3.3 Compact Wide-Area RTK Corrections 83 3.3.1 Satellite Orbit Corrections 86 3.3.2 Satellite Code/Phase Clock (CPC) Corrections 88 3.3.3 Tropospheric Corrections 89 3.3.4 Message Design for GEO Broadcasting 90 CHAPTER 4. Code/Phase Clock (CPC) Correction Generation Algorithm 93 4.1 Former Research of RTK Correction Protocol 93 4.1.1 Observation Based RTK Data Protocol 93 4.1.2 Correction Based RTK Data Protocol 95 4.1.3 Compact RTK Protocol 96 4.2 Satellite CPC Correction Generation Algorithm 100 4.2.1 Temporal Decorrelation Error Reduced Methods 102 4.2.2 Ambiguity Level Adjustment 105 4.2.3 Receiver Clock Synchronization 107 4.2.4 Averaging Filter of Satellite CPC Correction 108 4.2.5 Ambiguity Re-Initialization and Message Generation 109 4.3 Correction Performance Analysis Results 111 4.3.1 Feasibility Test Environments 111 4.3.2 Comparison of RTK Correction Protocol 113 4.3.3 Latency Compensation Performance Analysis 116 4.3.4 Message Data Bandwidth Analysis 119 CHAPTER 5. Tropospheric Correction Generation Algorithm 123 5.1 Former Research of Tropospheric Correction 123 5.1.1 Tropospheric Corrections for SBAS 124 5.1.2 Tropospheric Corrections of Network RTK 126 5.1.3 Tropospheric Corrections of PPP-RTK 130 5.2 Tropospheric Correction Generation Algorithm 136 5.2.1 ZWD Estimation Using Carrier-Phase Observations 138 5.2.2 ZWD Measurements Using Weather Data 142 5.2.3 Correction Generation Using Spherical Harmonics 149 5.2.4 Correction Applying Method for User 157 5.3 Correction Performance Analysis Results 159 5.3.1 Feasibility Test Environments 159 5.3.2 Zenith Correction Domain Analysis 161 5.3.3 Message Data Bandwidth Analysis 168 CHAPTER 6. Compact Wide-Area RTK User Test Results 169 6.1 Compact Wide-Area RTK User Process 169 6.2 User Performance Test Results 173 6.2.1 Feasibility Test Environments 173 6.2.2 User Range Domain Analysis 176 6.2.3 User Ambiguity Domain Analysis 182 6.2.4 User Position Domain Analysis 184 CHAPTER 7. Conclusions 189 Bibliography 193 ์ดˆ ๋ก 207Docto
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