Scholarlink

<p>Tropospheric delay is one of the primary error sources in GNSS and other radio signal-based positioning technologies. In precise point positioning (PPP), tropospheric delays significantly affect both convergence speed and positioning accuracy. Therefore, accurate tropospheric modeling is crucial for real-time high-precision positioning applications. Regional tropospheric modeling often employs low-order surface models. However, their formulations and accuracy require further optimization. To further enhance regional tropospheric modeling, this study introduces the Exponential Optimized Fitting Coefficients (EOFC) model. The EOFC model features a streamlined linearized formulation that reduces height-dependent polynomial terms while incorporating the strengths of the GPT3 empirical model. Using PPP-ZTD from reference station networks with varying spatial densities across inland and coastal regions of China, the model’s performance was validated. Results indicate that the EOFC model improves ZTD modeling accuracy by approximately 5% compared to the Modified Optimal Fitting Coefficients (MOFC) model, with seasonal gains reaching up to 9% in spring and 7% in autumn. In PPP-IAR experiments augmented with ZTD corrections derived from EOFC and MOFC, both models significantly enhanced positioning performance, with EOFC exhibiting greater improvement. Under a reference station spacing of 250&#xa0;km, convergence speeds improved by 10.0 and 9.1% for EOFC and MOFC, respectively. These findings demonstrate that the EOFC model not only simplifies the model structure but also achieves higher accuracy in regional tropospheric delay representation.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

An exponential optimized fitting coefficients wide-area tropospheric corrections model and its application in PPP-IAR

  • 期刊论文

  • 发表日期：

    2026年6月16日

查看全文
  • Xiaoting Lei,
  • Jing Guo,
  • Tianyu Yang,
  • Jun Tao,
  • Yihao Jiang,
  • Qile Zhao

摘要

Tropospheric delay is one of the primary error sources in GNSS and other radio signal-based positioning technologies. In precise point positioning (PPP), tropospheric delays significantly affect both convergence speed and positioning accuracy. Therefore, accurate tropospheric modeling is crucial for real-time high-precision positioning applications. Regional tropospheric modeling often employs low-order surface models. However, their formulations and accuracy require further optimization. To further enhance regional tropospheric modeling, this study introduces the Exponential Optimized Fitting Coefficients (EOFC) model. The EOFC model features a streamlined linearized formulation that reduces height-dependent polynomial terms while incorporating the strengths of the GPT3 empirical model. Using PPP-ZTD from reference station networks with varying spatial densities across inland and coastal regions of China, the model’s performance was validated. Results indicate that the EOFC model improves ZTD modeling accuracy by approximately 5% compared to the Modified Optimal Fitting Coefficients (MOFC) model, with seasonal gains reaching up to 9% in spring and 7% in autumn. In PPP-IAR experiments augmented with ZTD corrections derived from EOFC and MOFC, both models significantly enhanced positioning performance, with EOFC exhibiting greater improvement. Under a reference station spacing of 250 km, convergence speeds improved by 10.0 and 9.1% for EOFC and MOFC, respectively. These findings demonstrate that the EOFC model not only simplifies the model structure but also achieves higher accuracy in regional tropospheric delay representation.