Empirical Ionosphere-Constrained Uncombined Model for GNSS Rapid Ambiguity Resolution in Medium-to-Long Baseline Networks
Abstract
To address the issue of long ambiguity resolution (AR) time for existing medium-to-long baseline reference stations, this paper proposes a rapid ambiguity fixing method with empirical ionospheric constraints. The method directly treats the L1 and wide-lane (WL) ambiguities as unknown parameters to be estimated and performs synchronous filtering in the ambiguity domain. Furthermore, empirical ionospheric constraint factors are derived from real measurement data, thereby providing reasonable and effective variance constraints for the weighted estimation of ionospheric parameters. While accelerating ambiguity convergence, the proposed method also simplifies the solution procedure. Experimental results show that, compared with the classical ionosphere-free (IF) model, the proposed method significantly improves the accuracy of the ambiguity float solution and the baseline initialization speed. The RMS of the ambiguity float solution bias is reduced from 1.15 cycles to 0.45 cycles, representing an accuracy improvement of approximately 60.8%. The average baseline initialization time is shortened from 51.2 epochs to 21.7 epochs, corresponding to a speed enhancement of about 57.6%. In addition, the proposed method also markedly improves the ambiguity fixing speed for newly risen satellites at low elevation angles: the average time required for ambiguity fixing is reduced from 50.1 epochs to 14.8 epochs, and the average required elevation angle drops from 23.4° to 15.7°.