Bulletin of Surveying and Mapping ›› 2026, Vol. 0 ›› Issue (6): 14-22.doi: 10.13474/j.cnki.11-2246.2026.0603

Previous Articles     Next Articles

Quality analysis of multi-system data in the BeiDou ground-based augmentation system

LIAN Shuaijie1,2, CHENG Fang1,2,3, CUI Qingzhan1,2, SHEN Pengli1, GAO Xin1, HU Yuhang1,2, SUN Wenshuo1,2, LU Xiaochun1,2,3   

  1. 1. National Time Service Center, Chinese Academy of Sciences, Xi'an 710600, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China;
    3. Key Laboratory of Time Reference and Applications, Chinese Academy of Sciences, Xi'an 710600, China
  • Received:2025-10-22 Published:2026-07-09

Abstract: [Purposes] The quality of raw observations at reference stations is a critical factor in delivering high-precision services via the BeiDou ground-based augmentation system (BDS-GBAS),and a systemic quality analysis is of great significance for improving service accuracy and reliability.[Methods] This study analyzes observational data from five consecutive days at 110 domestic reference stations in the BDS-GBAS network.Using the Anubis software,we conduct data quality assessments in terms of completeness rate,cycle slips,multipath error,and carrier-to-noise ratio (C/No).[Findings]The results indicate that,91.8% of stations achieve a completeness rate above 85%; 99% of stations have a cycle slip rate (CSR)below 1 (per 1000); 99% of stations exhibit multipath error below 50 cm; 99% of stations have C/No above 40 dB·Hz,with the BDS system showing superior performance.We also identify a small number of anomalous stations,and propose possible causes and optimization suggestions based on station geographic location,antenna environment,etc.[Conclusions]The results confirm that the national BDS-GBAS network exhibits high overall observational quality.These findings provide important references for the layout,operational strategies,and data quality assurance of augmentation system reference stations.

Key words: BeiDou ground-based augmentation system, reference stations, Anubis, data quality, framework

CLC Number: