267 research outputs found

    Predicting the Success Rate of Long-baseline GPS+Galileo (Partial) Ambiguity Resolution

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    This contribution covers precise (cm-level) relative Global Navigation Satellite System(GNSS) positioning for which the baseline length can reach up to a few hundred km. Carrier-phase ambiguity resolution is required to obtain this high positioning accuracy within manageable observation time spans. However, for such long baselines, the differential ionospheric delays hamper fast ambiguity resolution as based on current dual-frequency Global Positioning System (GPS). It is expected that the modernization of GPS towards a triple-frequency system, as well as the development of Galileo towards a full constellation will be beneficial in speeding up long-baseline ambiguity resolution. In this article we will predict ambiguity resolution success rates for GPS+Galileo for a 250 km baseline based on the ambiguity variance matrix, where the Galileo constellation is simulated by means of Yuma almanac data. From our studies it can be concluded that ambiguity resolution will likely become faster (less than ten minutes) in the case of GPS+Galileo when based on triple frequency data of both systems, however much shorter times to fix the ambiguities (one-two minutes) can be expected when only a subset of ambiguities is fixed instead of the complete vector (partial ambiguity resolution)

    ์„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

    A comparison of TCAR, CIR and LAMBDA GNSS ambiguity resolution

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    With the envisioned introduction of three-carrier GNSS's (modernized GPS, Galileo), new methods of ambiguity resolution have been developed. In this contribution we will compare two important candidate methods for triple-frequency ambiguity resolution with the already existing LAMBDA (Least-squares Ambiguity Decorrelation Adjustment) method; the TCAR (Three-Carrier Ambiguity Resolution) method; and the CIR (Cascading Integer Resolution) method. It will be shown that for their estimation principle, both TCAR and CIR rely on integer bootstrapping, whereas LAMBDA is based on integer least-squares, of which optimality has been proven, that is, highest probability of success. In TCAR and CIR pre-defined ambiguity transformation are used, whereas LAMBDA exploits the information content of the full ambiguity variance-covariance matrix, with statistical decorrelation the objective in constructing the ambiguity transformation. For the aspect of resolving the ambiguities, TCAR and CIR are designed for use with the geometry-free model. LAMBDA can intrinsically handle any GNSS model with integer ambiguities and thereby utilize satellite geometry to its benefit in geometry-based models

    An analytical study of PPP-RTK corrections: precision, correlation and user-impact

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    PPP-RTK extends the PPP concept by providing single-receiver users, next to orbits and clocks, also information about the satellite phase and code biases, thus enabling single-receiver ambiguity resolution. It is the goal of the present contribution to provide an analytical study of the quality of the PPP-RTK corrections as well as of their impact on the user ambiguity resolution performance. We consider the geometry-free and the geometry-based network derived corrections, as well as the impact of network ambiguity resolution on these corrections. Next to the insight that is provided by the analytical solutions, the closed form expressions of the variance matrices also demonstrate how the corrections depend on network parameters such as number of epochs, number of stations, number of satellites, and number of frequencies. As a result we are able to describe in a qualitative sense how the user ambiguity resolution performance is driven by the data from the different network scenarios

    Array-Aided Multifrequency GNSS Ionospheric Sensing: Estimability and Precision Analysis

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    The dual-frequency Global Positioning System has proven to be an effective means of measuring the Earth's ionosphere and its total electron content (TEC). With the advent of multifrequency signals from more Global Navigation Satellite Systems (GNSSs), the opportunity arises to construct many more ionosphere-sensing combinations of GNSS data. With such diversity, various estimable ionospheric delays with differing interpretations (and of different precision) can be formed. How such estimable ionospheric delays should be interpreted, and the extent to which they contribute to the precision with which the unbiased TEC can be estimated, are the topics of this paper. Based on multifrequency GNSS code-only, phase-only, and phase-and-code data, we derive the closed-form solutions of different types of ionospheric observables that each can serve as input of an externally provided ionospheric model for TEC determination. Within such a general least-squares framework, we generalize the widely used phase-to-code levelling technique to its multifrequency version. We also show that only certain specific linear combinations of the observables contribute to the TEC solutions. As a further improvement of the multifrequency GNSS-derived TEC solution, we propose and study the usage of an array of GNSS antennas. Analytical solutions, supported by numerical examples, of this array-based concept are presented, together with a discussion on its relevance for TEC determination. This concerns the roles of time averaging and time differencing, of integer ambiguity resolution, and of the number of frequencies and number of array antennas in determining TEC

    Precise Point Positioning Augmentation for Various Grades of Global Navigation Satellite System Hardware

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    The next generation of low-cost, dual-frequency, multi-constellation GNSS receivers, boards, chips and antennas are now quickly entering the market, offering to disrupt portions of the precise GNSS positioning industry with much lower cost hardware and promising to provide precise positioning to a wide range of consumers. The presented work provides a timely, novel and thorough investigation into the positioning performance promise. A systematic and rigorous set of experiments has been carried-out, collecting measurements from a wide array of low-cost, dual-frequency, multi-constellation GNSS boards, chips and antennas introduced in late 2018 and early 2019. These sensors range from dual-frequency, multi-constellation chips in smartphones to stand-alone chips and boards. In order to be comprehensive and realistic, these experiments were conducted in a number of static and kinematic benign, typical, suburban and urban environments. In terms of processing raw measurements from these sensors, the Precise Point Positioning (PPP) GNSS measurement processing mode was used. PPP has become the defacto GNSS positioning and navigation technique for scientific and engineering applications that require dm- to cm-level positioning in remote areas with few obstructions and provides for very efficient worldwide, wide-array augmentation corrections. To enhance solution accuracy, novel contributions were made through atmospheric constraints and the use of dual- and triple-frequency measurements to significantly reduce PPP convergence period. Applying PPP correction augmentations to smartphones and recently released low-cost equipment, novel analyses were made with significantly improved solution accuracy. Significant customization to the York-PPP GNSS measurement processing engine was necessary, especially in the quality control and residual analysis functions, in order to successfully process these datasets. Results for new smartphone sensors show positioning performance is typically at the few dm-level with a convergence period of approximately 40 minutes, which is 1 to 2 orders of magnitude better than standard point positioning. The GNSS chips and boards combined with higher-quality antennas produce positioning performance approaching geodetic quality. Under ideal conditions, carrier-phase ambiguities are resolvable. The results presented show a novel perspective and are very promising for the use of PPP (as well as RTK) in next-generation GNSS sensors for various application in smartphones, autonomous vehicles, Internet of things (IoT), etc

    Precise GPS-based position, velocity and acceleration determination: algorithms and tools

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    Esta tesis doctoral llevรณ a cabo el estudio, desarrollo e implementaciรณn de algoritmos para la navegaciรณn con sistemas globales de navegaciรณn por satรฉlite (GNSS), enfocรกndose en la determinaciรณn precisa de la posiciรณn, velocidad y aceleraciรณn usando GPS, en modo post-procesado y lejos de estaciones de referencia. Uno de los objetivos era desarrollar herramientas en esta รกrea y hacerlas disponibles a la comunidad GNSS. Por ello el desarrollo se hizo dentro del marco del proyecto preexistente de software libre llamado GPS Toolkit (GPSTk). Una de las primeras tareas realizadas fue la validaciรณn de las capacidades de la GPSTk para el procesado del pseudorango, realizando comparaciones con una herramienta de procesamiento de datos probada (BRUS). La gestiรณn de datos GNSS demostrรณ ser un asunto importante cuando se intentรณ extender las capacidades de la GPSTk al procesamiento de datos obtenidos de las fases de la seรฑal GPS. Por ello se desarrollaron las Estructuras de Datos GNSS (GDS), que combinadas con su paradigma de procesamiento aceleran el proceso de desarrollo de software y reducen errores. La extensiรณn de la GPSTk a los algoritmos de procesado en fase se hizo mediante la ayuda de las GDS, proporcionรกndose importantes clases accesorias que facilitan el trabajo. Se implementรณ el procesado de datos Precise Point Positioning (PPP) con ejemplos relativamente simples basados en las GDS, y al comparar sus resultados con otras aplicaciones de reputaciรณn ya establecida, se encontrรณ que destacan entre los mejores. Tambiรฉn se estudiรณ cรณmo obtener la posiciรณn precisa, en post-proceso, de un receptor GPS a cientos de kilรณmetros de la estaciรณn de referencia mรกs cercana y usando tasas de datos arbitrarias (una limitaciรณn del mรฉtodo PPP). Las ventajas aportadas por las GDS permitieron la implementaciรณn de un procesado semejante a un PPP cinemรกtico basado en una red de estaciones de referencia, estrategia bautizada como Precise Orbits Positioning (POP) porque sรณlo necesita รณrbitas precisas para trabajar y es independiente de la informaciรณn de los relojes de los satรฉlites GPS. Los resultados de este enfoque fueron muy similares a los del mรฉtodo PPP cinemรกtico estรกndar, pero proporcionando soluciones de posiciรณn con una tasa mayor y de manera mรกs robusta. La รบltima parte se enfocรณ en la implementaciรณn y mejora de algoritmos para determinar con precisiรณn la velocidad y aceleraciรณn de un receptor GPS. Se hizo รฉnfasis en el mรฉtodo de las fases de Kennedy debido a su buen rendimiento, desarrollando una implementaciรณn de referencia y demostrando la existencia de una falla en el procedimiento propuesto originalmente para el cรกlculo de las velocidades de los satรฉlites. Se propuso entonces una modificaciรณn relativamente sencilla que redujo en un factor mayor que 35 el RMS de los errores 3D en velocidad. Tomando ideas de los mรฉtodos Kennedy y POP se desarrollรณ e implementรณ un nuevo procedimiento de determinaciรณn de velocidad y aceleraciรณn que extiende el alcance. Este mรฉtodo fue llamado Extended Velocity and Acceleration determination (EVA). Un experimento usando una aeronave ligera volando sobre los Pirineos mostrรณ que tanto el mรฉtodo de Kennedy (modificado) como el mรฉtodo EVA son capaces de responder ante la dinรกmica de este tipo de vuelos. Finalmente, tanto el mรฉtodo de Kennedy modificado como el mรฉtodo EVA fueron aplicados a una red en la zona ecuatorial de Sur Amรฉrica con lรญneas de base mayores a 1770 km. En este escenario el mรฉtodo EVA mostrรณ una clara ventaja tanto en los promedios como en las desviaciones estรกndar para todas las componentes de la velocidad y la aceleraciรณn.This Ph.D. Thesis focuses on the development of algorithms and tools for precise GPS-based position, velocity and acceleration determination very far from reference stations in post-process mode. One of the goals of this thesis was to develop a set of state-of-the-art GNSS data processing tools, and make them available for the research community. Therefore, the software development effort was done within the frame of a preexistent open source project called the GPSTk. Therefore, validation of the GPSTk pseudorange-based processing capabilities with a trusted GPS data processing tool was one of the initial task carried out in this work. GNSS data management proved to be an important issue when trying to extend GPSTk capabilities to carrier phasebased data processing algorithms. In order to tackle this problem the GNSS Data Structures (GDS) and their associated processing paradigm were developed. With this approach the GNSS data processing becomes like an assembly line, providing an easy and straightforward way to write clean, simple to read and use software that speeds up development and reduces errors. The extension of GPSTk capabilities to carrier phase-based data processing algorithms was carried out with the help of the GDS, adding important accessory classes necessary for this kind of data processing and providing reference implementations. The performance comparison of these relatively simple GDS-based source code examples with other state-of-the art Precise Point Positioning (PPP) suites demonstrated that their results are among the best. Furthermore, given that the GDS design is based on data abstraction, it allows a very flexible handling of concepts beyond mere data encapsulation, including programmable general solvers, among others. The problem of post-process precise positioning of GPS receivers hundreds of kilometers away from nearest reference station at arbitrary data rates was dealt with, overcoming an important limitation of classical post-processing strategies like PPP. The advantages of GDS data abstraction regarding solvers were used to implement a kinematic PPP-like processing based on a network of stations. This procedure was named Precise Orbits Positioning (POP) because it is independent of precise clock information and it only needs precise orbits to work. The results from this approach were very similar (as expected) to the standard kinematic PPP processing strategy, but yielding a higher positioning rate. Also, the network-based processing of POP seems to provide additional robustness to the results, even for receivers outside the network area. The last part of this thesis focused on implementing, improving and testing algorithms for the precise determination of velocity and acceleration hundreds of kilometers away from nearest reference station. Special emphasis was done on the Kennedy method because of its good performance. A reference implementation of Kennedy method was developed, and several experiments were carried out. Experiments done with very short baselines showed a flaw in the way satellite velocities were computed, introducing biases in the velocity solution. A relatively simple modification was proposed, and it reduced the RMS of 5-min average velocity 3D errors by a factor of over 35. Then, borrowing ideas from Kennedy method and the POP method, a new velocity and acceleration determination procedure named EVA was developed and implemented that greatly extends the effective range. An experiment using a light aircraft flying over the Pyrenees showed that both the modified-Kennedy and EVA methods were able to cope with the dynamics of this type of flight. Finally, both modified-Kennedy and EVA method were applied to a challenging scenario in equatorial South America, with baselines over 1770 km, where EVA method showed a clear advantage in both averages and standard deviations for all components of velocity and acceleration. Lloc

    Performance of precise marine positioning using future modernised global satellite positioning systems and a novel partial ambiguity resolution technique

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    The International Maritime Organisation (IMO) established a set of positioning requirements for future Global Navigation Satellite System (GNSS) constellations in IMO resolution A.915. It is important to be able to determine if these requirements can be met, and what shore infrastructure would be required. This thesis describes the collection of data in a marine environment and the analysis of these data with regards to the requirements. The data collection exercise was held at the beginning of May 2008 and saw THV Alert navigate into Harwich Harbour whilst Global Positioning System (GPS) observation data were recorded from onboard the vessel and from shore-based reference stations. Additional data were obtained from nearby Ordnance Survey reference stations, and two total stations were used to track the vesselโ€™s passage to provide a truth model. Several modernised GPS satellites were tracked. The data were processed under different scenarios, using software developed at UCL, and the positioning performance was analysed in the context of the IMO requirements. Potential performance improvements from modernised GPS and Galileo were then discussed. Providing integrity through single-epoch real-time kinematic positioning, required to meet the strictest IMO requirements, is particularly difficult. The identification of phase observation outliers is not possible before the integer ambiguities are resolved, but an undetected outlier could prevent successful ambiguity resolution. It will not always be necessary to fix all the ambiguities to achieve the required positioning precision, particularly with a multi-GNSS constellation. This thesis introduces a new algorithm for partial ambiguity resolution in the presence of measurement bias. Although computationally intensive, this algorithm significantly improves the ambiguity resolution success rate, increasing the maximum baseline length over which the highest requirements are met with dual-frequency GPS from 1 km to 66 km

    Multi-frequency and multi-GNSS PPP phase bias estimation and ambiguity resolution

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    BDS GNSS for Earth Observation

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    For millennia, human communities have wondered about the possibility of observing phenomena in their surroundings, and in particular those affecting the Earth on which they live. More generally, it can be conceptually defined as Earth observation (EO) and is the collection of information about the biological, chemical and physical systems of planet Earth. It can be undertaken through sensors in direct contact with the ground or airborne platforms (such as weather balloons and stations) or remote-sensing technologies. However, the definition of EO has only become significant in the last 50 years, since it has been possible to send artificial satellites out of Earthโ€™s orbit. Referring strictly to civil applications, satellites of this type were initially designed to provide satellite images; later, their purpose expanded to include the study of information on land characteristics, growing vegetation, crops, and environmental pollution. The data collected are used for several purposes, including the identification of natural resources and the production of accurate cartography. Satellite observations can cover the land, the atmosphere, and the oceans. Remote-sensing satellites may be equipped with passive instrumentation such as infrared or cameras for imaging the visible or active instrumentation such as radar. Generally, such satellites are non-geostationary satellites, i.e., they move at a certain speed along orbits inclined with respect to the Earthโ€™s equatorial plane, often in polar orbit, at low or medium altitude, Low Earth Orbit (LEO) and Medium Earth Orbit (MEO), thus covering the entire Earthโ€™s surface in a certain scan time (properly called โ€™temporal resolutionโ€™), i.e., in a certain number of orbits around the Earth. The first remote-sensing satellites were the American NASA/USGS Landsat Program; subsequently, the European: ENVISAT (ENVironmental SATellite), ERS (European Remote-Sensing satellite), RapidEye, the French SPOT (Satellite Pour lโ€™Observation de laTerre), and the Canadian RADARSAT satellites were launched. The IKONOS, QuickBird, and GeoEye-1 satellites were dedicated to cartography. The WorldView-1 and WorldView-2 satellites and the COSMO-SkyMed system are more recent. The latest generation are the low payloads called Small Satellites, e.g., the Chinese BuFeng-1 and Fengyun-3 series. Also, Global Navigation Satellite Systems (GNSSs) have captured the attention of researchers worldwide for a multitude of Earth monitoring and exploration applications. On the other hand, over the past 40 years, GNSSs have become an essential part of many human activities. As is widely noted, there are currently four fully operational GNSSs; two of these were developed for military purposes (American NAVstar GPS and Russian GLONASS), whilst two others were developed for civil purposes such as the Chinese BeiDou satellite navigation system (BDS) and the European Galileo. In addition, many other regional GNSSs, such as the South Korean Regional Positioning System (KPS), the Japanese quasi-zenital satellite system (QZSS), and the Indian Regional Navigation Satellite System (IRNSS/NavIC), will become available in the next few years, which will have enormous potential for scientific applications and geomatics professionals. In addition to their traditional role of providing global positioning, navigation, and timing (PNT) information, GNSS navigation signals are now being used in new and innovative ways. Across the globe, new fields of scientific study are opening up to examine how signals can provide information about the characteristics of the atmosphere and even the surfaces from which they are reflected before being collected by a receiver. EO researchers monitor global environmental systems using in situ and remote monitoring tools. Their findings provide tools to support decision makers in various areas of interest, from security to the natural environment. GNSS signals are considered an important new source of information because they are a free, real-time, and globally available resource for the EO community
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