Improving precise point positioning (PPP) performance with best integer equivariant (BIE) estimator

Precise point positioning (PPP) technology is capable of providing global high-precision positioning services, but its main application bottleneck is the long convergence time. Accurate and reliable carrier phase ambiguity resolution (AR) is a primary approach to accelerate PPP convergence and improve its accuracy. The best integer equivariant (BIE) method, known for its superior performance in minimizing mean square error (MSE), is gradually being adopted for PPP-AR. This study examines key aspects of the BIE algorithm, including the determination of the optimal number of candidate sets and how the number of candidates evolves during convergence. The performance of the BIE algorithm is evaluated by utilizing both post-processing products and real-time products generated at the French CNES (Centre National D'Etudes Spatiales) with static station data. The experimental results unequivocally demonstrate that the BIE algorithm significantly improves both positioning accuracy and convergence speed compared to the least-squares ambiguity decorrelation adjustment (LAMBDA) algorithm in PPP-AR. Furthermore, a verification experiment using real ship-borne dynamic data confirms the exceptional robustness of the BIE algorithm.