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<p>Currently, four dominant Global Navigation Satellite Systems (GNSS), namely GPS (G), Galileo (E), GLONASS (R), and BDS-3 (C), provide multi-frequency positioning services on a global scale. To fully harness the potential of multi-system and multi-frequency signals for precise point positioning (PPP), a triple-frequency PPP ambiguity resolution (PPP-AR) model by integrating observations from GLONASS, GPS, Galileo, and BDS-3 is presented for the first time. Particular attention was given to incorporating newly available signals, such as GLONASS code-division multiple-access (CDMA) L3 and BDS-3 B2a, into the proposed GERC triple-frequency PPP-AR framework to realize instantaneous convergence. To address the challenges posed by GLONASS inter-frequency biases (IFBs) inherent to its frequency-division multiple-access (FDMA) strategy, we introduced an uncalibrated phase delay (UPD) estimation method based on homogeneous receiver networks. Additionally, inter-frequency clock biases (IFCBs) across multiple systems were comprehensively determined and calibrated within the GERC triple-frequency PPP-AR context. To validate the proposed model, observational datasets from 20 EUREF Permanent Network (EPN) tracking stations equipped with identical JAVAD receivers were processed. The quality of UPD estimates was evaluated through residual distribution analysis, revealing a strong correlation between UPD correction accuracy and the magnitude of residuals. Results showed that nearly 100% of extra-wide lane (EWL) ambiguity residuals for each GNSS constellation were within 0.15 cycles. Furthermore, more than 95% of wide lane (WL) and narrow lane (NL) ambiguity residuals were below 0.25 cycles. Statistical analysis demonstrated that the GERC triple-frequency PPP-AR achieved an instantaneous convergence time of approximately 0.71&#xa0;min, significantly outperforming single-system PPP-AR solutions such as G (7.32&#xa0;min), GR (4.95&#xa0;min), GC (3.10&#xa0;min), and GE (1.39&#xa0;min). Compared to the dual-frequency GERC PPP-AR (1.82&#xa0;min), the triple-frequency solution improved convergence time by approximately 61%. These results are highly encouraging, as they demonstrate that multi-GNSS PPP-AR solutions can achieve sub-minute convergence times with enhanced positioning accuracy. In addition, simulated kinematic PPP-AR experiments further confirmed the superiority of the GERC triple-frequency scheme. The convergence time was reduced to approximately 3.43&#xa0;min, significantly outperforming the triple-frequency GEC scheme (4.68&#xa0;min) and the dual-frequency GERC scheme (5.25&#xa0;min). The incorporation of GLONASS L3 observations proved vital for enhancing PPP-AR performance.</p>

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Achieving PPP instantaneous convergence with the integration of GLONASS/GPS/BDS-3/Galileo triple-frequency observations

  • 期刊论文

  • 发表日期：

    2025年12月24日

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  • Fan Zhang,
  • Wei Lu,
  • Fan Gao,
  • Linlu Gan,
  • Tao Liu

摘要

Currently, four dominant Global Navigation Satellite Systems (GNSS), namely GPS (G), Galileo (E), GLONASS (R), and BDS-3 (C), provide multi-frequency positioning services on a global scale. To fully harness the potential of multi-system and multi-frequency signals for precise point positioning (PPP), a triple-frequency PPP ambiguity resolution (PPP-AR) model by integrating observations from GLONASS, GPS, Galileo, and BDS-3 is presented for the first time. Particular attention was given to incorporating newly available signals, such as GLONASS code-division multiple-access (CDMA) L3 and BDS-3 B2a, into the proposed GERC triple-frequency PPP-AR framework to realize instantaneous convergence. To address the challenges posed by GLONASS inter-frequency biases (IFBs) inherent to its frequency-division multiple-access (FDMA) strategy, we introduced an uncalibrated phase delay (UPD) estimation method based on homogeneous receiver networks. Additionally, inter-frequency clock biases (IFCBs) across multiple systems were comprehensively determined and calibrated within the GERC triple-frequency PPP-AR context. To validate the proposed model, observational datasets from 20 EUREF Permanent Network (EPN) tracking stations equipped with identical JAVAD receivers were processed. The quality of UPD estimates was evaluated through residual distribution analysis, revealing a strong correlation between UPD correction accuracy and the magnitude of residuals. Results showed that nearly 100% of extra-wide lane (EWL) ambiguity residuals for each GNSS constellation were within 0.15 cycles. Furthermore, more than 95% of wide lane (WL) and narrow lane (NL) ambiguity residuals were below 0.25 cycles. Statistical analysis demonstrated that the GERC triple-frequency PPP-AR achieved an instantaneous convergence time of approximately 0.71 min, significantly outperforming single-system PPP-AR solutions such as G (7.32 min), GR (4.95 min), GC (3.10 min), and GE (1.39 min). Compared to the dual-frequency GERC PPP-AR (1.82 min), the triple-frequency solution improved convergence time by approximately 61%. These results are highly encouraging, as they demonstrate that multi-GNSS PPP-AR solutions can achieve sub-minute convergence times with enhanced positioning accuracy. In addition, simulated kinematic PPP-AR experiments further confirmed the superiority of the GERC triple-frequency scheme. The convergence time was reduced to approximately 3.43 min, significantly outperforming the triple-frequency GEC scheme (4.68 min) and the dual-frequency GERC scheme (5.25 min). The incorporation of GLONASS L3 observations proved vital for enhancing PPP-AR performance.