Synergistic augmentation of BDS PPP-B2b: integrating LEO constellations and wide-lane ambiguity resolution for instantaneous convergence

北斗PPP-B2b的协同增强:整合低地球轨道星座和宽车道模糊度解算以实现瞬时收敛

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Abstract

To address the slow convergence issue of PPP-B2b, this paper proposes a positioning method that integrates wide-lane ambiguity resolution (WAR) with low earth orbit (LEO) synergistic enhancement. First, based on an uncombined precise point positioning (PPP) model that accounts for the clock constant bias (CCB), the extra-wide lane (EWL) and wide-lane (WL) fractional cycle biases (FCBs) for GPS/BDS-3 were extracted. Subsequently, two hybrid LEO constellations with scales of 96 and 144 satellites were designed, and multi-frequency observations were simulated. Finally, four sets of progressive experiments (float solution, wide-lane fixed solution, LEO-enhanced float solution, and synergistic enhanced solution) were designed to evaluate the enhancement performance. The results demonstrate that both WAR and LEO enhancement can improve the accuracy and convergence performance of PPP-B2b, with temporal complementarity during the convergence stage. Specifically, WAR enhancement improves the initial epoch accuracy to decimeter-level and reduces the average convergence time by over 30%, while LEO enhancement requires multiple epoch accumulations but achieves or even surpasses the WAR enhancement within a short time (e.g., 20-40 s) due to its rapid geometric variation advantage, reducing the average convergence time from approximately 20 min to 1-2 min. The synergistic enhancement of both methods balances the initial epoch parameter estimation accuracy and rapid convergence advantage, achieving improvements in average accuracy and convergence time of over 70% and 90%, respectively.

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