An increasing number of reference stations have been established, leading to a sharp increase in the workload of Double-Difference (DD) baseline solutions, which are not appropriate for the integrated processing of denser networks. Correlations among the ambiguities in DD models are complex, and it is difficult to get precise solutions. This paper improves the DD ambiguity resolution performance over a long baseline, using a modified strategy based on an Un-Differenced (UD) and Un-Combined (UC) model. The satellite clocks are estimated as parameters, which are properly constrained by real-time satellite clock products for improving the smoothness of ambiguities. We use data from the Earth Scope Plate Boundary Observatory to examine the presented method in Global Positioning System (GPS) networks. Our method obtained more obviously centralised distributions. The successful fixed rate was 96·4% for the DD baseline solution, and 98·4% for the UD method. The proposed strategy is appropriate for the distributed architecture of extensive systems and avoids a heavy computational burden.