다중 위성 GNSS PPP 정확도 향상을 위한 거리, 고도각 및 SNR 기반 가중값 모델 개발

Multi- Global Navigation Satellite System (GNSS) integration is widely recognized as an effective approach to improve positioning accuracy and reduce convergence time. However, issues of performance degradation regarding certain satellite constellations have been raised, particularly some BeiDou sat...

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Bibliographic Details
Published inJournal of Positioning, Navigation, and Timing Vol. 14; no. 2; pp. 149 - 155
Main Authors 이형석, 한정민, 박관동, Hyung-Seok Lee, Jeong-Min Han, Kwan-Dong Park
Format Journal Article
LanguageKorean
Published 사단법인 항법시스템학회 01.06.2025
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ISSN2288-8187
2289-0866
DOI10.11003/JPNT.2025.14.2.149

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Summary:Multi- Global Navigation Satellite System (GNSS) integration is widely recognized as an effective approach to improve positioning accuracy and reduce convergence time. However, issues of performance degradation regarding certain satellite constellations have been raised, particularly some BeiDou satellites in Geostationary Earth Orbit (GEO), due to orbit-related errors. To address this, the present study proposes a novel weighting model that maintains the advantages of multi-GNSS integration while minimizing the adverse effects by applying differential weights based on satellite constellation characteristics. The proposed model calculates satellite weights by comprehensively considering satellite-to-receiver range, elevation angle, and signal-to-noise ratio (SNR), and quantitatively reflects the physical characteristics of each constellation-Medium Earth Orbit (MEO), Inclined Geosynchronous Orbit (IGSO), and GEO. Using GNSS data collected over a 12-hour period, this study applies a least-squares-based Precise Point Positioning method using pseudorange measurements with State Space Representation (SSR) corrections. The positioning performance of two weighting strategies is compared: one using elevation and SNR, and the other incorporating range, elevation, and SNR. The results show that the model considering all three factors-range, elevation, and SNR-improved the average positioning accuracy by 3.1%, with a maximum improvement of 9.7%. Additionally, a low standard deviation of 4.1% indicates consistent performance enhancement, and demonstrates the effectiveness of the proposed differential weighting approach.
Bibliography:KISTI1.1003/JNL.JAKO202516850406237
https://doi.org/10.11003/JPNT.2025.14.2.149
ISSN:2288-8187
2289-0866
DOI:10.11003/JPNT.2025.14.2.149