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<p>The real-time precise point positioning (RT-PPP) service of BDS-3 (PPP-B2b) was launched in July 2021 to deliver a decimeter-level positioning service for users in China and its surrounding areas. During the use of PPP-B2b, we identified two issues adversely affecting positioning performance: systematic jumps in GPS clock bias and inaccuracies of the URA parameter. This paper analyzes the impact of these issues on PPP performance and proposes practical solutions. To address the GPS clock bias, we introduce three user-side strategies, including a jump detection and clock splicing method combined with various inter-system bias (ISB) estimation strategies. Performance comparisons reveal that effective bias processing can reduce the three-dimensional root-mean-square error (RMSE) from 0.83 to 0.08&#xa0;m in kinematic mode. Additionally, we validate the insufficient accuracy of broadcasted URA and propose an approach to re-estimate the phase URA using data from over 50 monitoring stations across China, demonstrating that the refined URA enhances the PPP-B2b positioning stochastic model and this provides a viable direction for optimizing the PPP-B2b service.</p>

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Clock systematic jump estimation and URA refinement of BDS-3 B2b real-time precise point positioning service

  • 期刊论文

  • 发表日期：

    2025年3月4日

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  • Junping Chen,
  • Ziyuan Song,
  • Yize Zhang,
  • Junsheng Ding,
  • Xin Jiang,
  • Sainan Yang,
  • Yangfei Hou

摘要

The real-time precise point positioning (RT-PPP) service of BDS-3 (PPP-B2b) was launched in July 2021 to deliver a decimeter-level positioning service for users in China and its surrounding areas. During the use of PPP-B2b, we identified two issues adversely affecting positioning performance: systematic jumps in GPS clock bias and inaccuracies of the URA parameter. This paper analyzes the impact of these issues on PPP performance and proposes practical solutions. To address the GPS clock bias, we introduce three user-side strategies, including a jump detection and clock splicing method combined with various inter-system bias (ISB) estimation strategies. Performance comparisons reveal that effective bias processing can reduce the three-dimensional root-mean-square error (RMSE) from 0.83 to 0.08 m in kinematic mode. Additionally, we validate the insufficient accuracy of broadcasted URA and propose an approach to re-estimate the phase URA using data from over 50 monitoring stations across China, demonstrating that the refined URA enhances the PPP-B2b positioning stochastic model and this provides a viable direction for optimizing the PPP-B2b service.