166 research outputs found

    Non-Taylor series based positioning method for location based services

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    Location Based Services (LBS) has gained increasing popularity in major cities. Due to blocking from man-made structures, the existing Global Positioning System (GPS) could not satisfy LBS applications, especially in street canyon and indoor surroundings. This has lead to the development of Assisted GPS (A-GPS) which can provide better service availability and accuracy gain. In the conventional positioning method, Taylor series expansion is applied to solve non-linear distance equations. This method requires an initial estimation of A-GPS receiverโ€™s position. This paper investigates the positioning method for LBS based on hybrid E-OTD/GNSS. The proposed positioning method is non-Taylor series based. Therefore, it involves less complicated mathematical expansion and substitution. A flexible LBS positioning tool is developed which can generate position information in convenient way. It supports both Taylor series and non-Taylor series based positioning methods. The obtained results showed that the proposed non-Taylor series based positioning method can achieve better positioning accuracy

    Multi-purpose TDM Component for GNSS

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    International audienceThis article proposes a Time-Division-Multiplexing (TDM) technique applied at PRN code level as a signal design solution able to cope with the provision of several functionalities in one signal component: the allocation of the signal to the different functionalities is made at PRN code level. The functionalities targeted in this article are low-complexity acquisition, fast Time-ToFirst-Fix Data (TTFFD), Security Code Authentication (SCA) and, additionally, non-coherent signal processing. The interest of using a TDM component signal design lays on the introduction of just one new component to reduce the complexity to be added to the legacy GNSS satellite payload and to the GNSS receiver. Moreover, a TDM signal design solution presents a great flexibility able to adapt the signal design to the different GNSS strategic directives. The TDM component is constituted of period blocks called short basic blocks and advanced blocks; the introduction of such blocks simplifies the TDM component processing by a GNSS receiver. The TDM component is divided first in a continuous stream of short basic blocks of 20ms, where the short basic blocks are used to provide a signal periodic structure for the acquisition functionality. Then, the short basic blocks are grouped in advanced blocks to provide the signal periodicity for fast TTFFD and SCA. The low-complexity acquisition functionality is provided by the first PRN codes of a short basic block: PRN codes are selected to have a low duration and are always at the same position inside the block. Code Shift Keying Modulation is used to provide the fast TTFFD and the SCA key delivery. An example of application on the Galileo E1 civil signals is presented with different target scenarios or type of users: lowcomplexity user, high performance โ€“ no TTFFD, high performance โ€“ TTFFD and high dynamics user

    A New Cooperative PPP-RTK System with Enhanced Reliability in Challenging Environments

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    Compared to the traditional PPP-RTK methods, cooperative PPP-RTK methods provide expandable service coverage and eliminate the need for a conventional expensive data processing center and the establishment and maintenance of a permanently deployed network of dense GNSS reference stations. However, current cooperative PPP-RTK methods suffer from some major limitations. First, they require a long initialization period before the augmentation service can be made available from the reference stations, which decreases their usability in practical applications. Second, the inter-reference station baseline ambiguity resolution (AR) and regional atmospheric model, as presented in current state-of-art PPP-RTK and network RTK (NRTK) methods, are not utilized to improve the accuracy and service coverage of the network augmentation. Third, the positioning performance of current PPP-RTK methods would be significantly degraded in challenging environments due to multipath effects, non-line-of-sight (NLOS) errors, poor satellite visibility and geometry caused by severe signal blockages. Finally, current position domain or ambiguity domain partial ambiguity resolution (PAR) methods suffer from high false alarm and miss detection, particularly in challenging environments with poor satellite geometry and observations contaminated by NLOS effect, gross errors, biases, and high observation noise. This thesis proposed a new cooperative PPP-RTK positioning system, which offers significant improvements to provide fast-initialization, scalable coverage, and decentralized real-time kinematic precise positioning with enhanced reliability in challenging environments. The system is composed of three major components. The first component is a new cooperative PPP-RTK framework in which a scalable chain of cooperative static or moving reference stations, generates single reference station-derived or reference station network-derived state-space-representation (SSR) corrections for fast ambiguity resolution at surrounding user stations with no need for a conventional expensive data processing center. The second component is a new multi-feature support vector machine (SVM) signal classifier based weight scheme for GNSS measurements to improve the kinematic GNSS positioning accuracy in urban environments. The weight scheme is based on the identification of important features in GNSS data in urban environments and intelligent classification of line-of-sight (LOS) and NLOS signals. The third component is a new PAR method based on machine learning, which employs the combination of two support vector machine (SVM) to effectively identify and exclude bias sources from PAR without relying on satellite geometry. The prototype of the new PPP-RTK system is developed and substantially tested using publically available real-time SSR products from International GNSS Service (IGS) Real-Time Service (RTS)

    ์„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

    Modeling wide-area tropospheric delay corrections for fast PPP ambiguity resolution

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    The performance of precise point positioning (PPP) has been significantly improved thanks to the continuous improvements in satellite orbit, clock, and ambiguity resolution (AR) technologies, but the convergence speed remains a limiting factor in real-time PPP applications. To improve the PPP precision and convergence time, tropospheric delays from a regional network can be modeled to provide precise correction for users. We focus on the precise modeling of zenith wet delay (ZWD) over a wide area with large altitude variations for improving PPP-AR. By exploiting the water vapor exponential vertical decrease, we develop a modified optimal fitting coefficients (MOFC) model based on the traditional optimal fitting coefficients (OFC) model. The proposed MOFC model provides a precision better than 1.5 cm under sparse inter-station distances over the Europe region, with a significant improvement of 70% for high-altitude stations compared to the OFC model. The MOFC model with different densities of reference stations is further evaluated in GPS and Galileo kinematic PPP-AR solutions. Compared to the PPP-AR solutions without tropospheric delay augmentation, the positioning precision of those with 100-km inter-station spacing MOFC and OFC is improved by 25.7% and 17.8%, respectively, and the corresponding time to first fix (TTFF) is improved by 36.9% and 33.0% in the high-altitude areas. On the other hand, the OFC model only slightly improves the TTFF and positioning accuracy when using the 200 km inter-station spacing modeling and even degrades the positioning for high-altitude stations, whereas using the MOFC model, the PPP-AR solutions always improve. Moreover, the positioning precision improvement of MOFC compared with OFC is about 22.1%, 21.7%, and 25.7% for the Galileo-only, GPS-only, and GPSโ€‰+โ€‰Galileo PPP-AR solutions, respectively

    Snapshot Estimation Algorithms for GNSS Mass-Market Receivers

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    This thesis resumes the PhD program carried out in the signal processing, satellite positioning and telecommunication fields, within the Navigation, Signal Analysis and Simulation (NavSAS) group, Department of Electronics and Telecommunications (DET) of Politecnico di Torino, in the period going from January 2012 to December 2014. The main topic of the PhD activity is represented by Global Navigation Satellite System (GNSS) receivers core technologies. In particular, it deals with the design, development, test and performance assessment of innovative architectures, techniques, and algorithms for Global Positioning System (GPS) and Galileo receivers, both professional high performance and commercial mass-market. GPS, and in general GNSSs are radio-communication infrastructures, aimed to enable a generic user to compute Position, Velocity and Time (PVT). The signals transmitted by a constellation of satellites are processed by an electronic device, performing trilateration with respect to the satellites, taken as reference points. At least 4 satellites are required to be in Line of Sight (LOS) with the receiver, so as to obtain 4 different signals and to solve the 4 navigation unknowns: latitude, longitude, height and time. Since their first appearance, in the early seventies, GNSS chipsets and devices are gaining a fundamental role in most applications of everyday life, and their global market continues to grow rapidly. In 25 years, GNSS receivers became extremely used worldwide, not only for positioning and navigation purposes, but also for time synchronization, thus spanning an unlimited range of applications, from commercial to scientific, from military to recreational. GNSS mass-market receivers are extremely widespread, produced in very high volumeโ€”hundreds of millions just for smartphones and tabletsโ€”and sold at a limited price. This variety of applications and possibilities represents the main reason of the continuous growth of the GNSS field: in fact, new systems are emerging beside GPS, such as GLONASS, currently operational and in expansion, Galileo and Beidou. With the latest trends of multi-constellation receivers, the positioning accuracy can greatly improve, as well as its robustness, availability, reliability, but at the expense of a greater complexity and power consumption

    FLAMINGO โ€“ Fulfilling enhanced location accuracy in the mass-market through initial GalileO services

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    This paper discusses FLAMINGO, an initiative that will provide a high accuracy positioning service to be used by mass market applications. The status and future for the initiative are discussed, the required accuracies and other location parameters are described, and the target applications are identified. Finally, the currently achieved accuracies from todayโ€™s Smartphones are assessed and presented. FLAMINGO (Fulfilling enhanced Location Accuracy in the Mass-market through Initial GalileO services), part funded through the European GNSS Agency, is a collaborative venture comprising NSL (as lead organization), Telespazio France, University of Nottingham, Rokubun, Thales Alenia Space France, VVA, BQ, ECLEXYS and Blue Dot Solutions. The initiative is developing the infrastructure, solutions and services to enable the use of accurate and precise GNSS within the mass-market, thereby operating predominantly in an urban environment. Whilst mass-market receivers are yet to achieve accuracies below one metre for standard positioning, the introduction of Android raw GNSS measurements and the Broadcom dual frequency chipset (BCM47755), has presented the devices such an opportunity. FLAMINGO will enable and demonstrate the future of high accuracy positioning and navigation information on mass-market devices such as smartphones and Internet of Things (IoT) devices by producing a service delivering accuracies of 50cm (at 95%) and better, employing multi-constellation, PPP and RTK mechanisms, power consumption optimisation techniques. Whereas the Galileo High Accuracy Service targets 10cm precision within professional markets, FLAMINGO targets 30-50cm precision in the mass-market consumer markets. By targeting accuracies of a few decimetres, a range of improved and new applications in diverse market sectors are introduced. These sectors include, but are not limited to, mapping and GIS, autonomous vehicles, AR environments, mobile-location based gaming and people tracking. To obtain such high accuracies with mass market devices, FLAMINGO must overcome several challenges which are technical, operational and environmental. This includes the hardware capabilities of most mass-market devices, where components such as antennas and processors are prioritised for other purposes. We demonstrate that, despite these challenges, FLAMINGO has the potential to meet the accuracy required. Tests with the current Smartphones that provide access to multi-constellation raw measurements (the dual frequency Xiaomi Mi 8 and single frequency Samsung S8 and Huawei P10) demonstrate significant improvements to the PVT solution when processing using both RTK and PPP techniques

    Link-Layer Coding for GNSS Navigation Messages

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    In this paper, we face the problem of ensuring reliability of Global Navigation Satellite Systems (GNSSs) in harsh channel conditions, where obstacles and scatter cause long outage events that cannot be counteracted with channel coding only. Our novel approach, stemming from information-theoretic considerations, is based on link-layer coding (LLC). LLC allows us to significantly improve the efficiency in terms of time-to-first-fix with respect to current operational GNSSs, which adopt carousel transmission. First, we investigate the maximum theoretical LLC gain under different Land Mobile Satellite channel conditions. Then, some practical LLC coding schemes, namely, fountain codes and a novel low-density parity-check plus low-rate repetition coding, are proposed and tested in realistic single-satellite and multi-satellite Land Mobile Satellite scenarios, considering the Galileo I/NAV message as study case. Simulation results show that our designed schemes largely improve on carousel transmission and achieve near-optimal performance with limited increase in complexity. Also, back-compatibility of LLC is assessed with respect to present-time GNSS specifications. ยฉ 2018 Institute of Navigation
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