To address the problem that traditional crossover positioning methods for massive multi-source satellite altimetry data struggle to balance accuracy and efficiency, a novel DWCC(dynamic window constrained crossover) algorithm was developed by integrating polynomial fitting with the principle of orbital symmetry. A multi-level constraint mechanism, combining spatial pre-screening and computer graphics logic, was constructed to eliminate redundant computations. The solution was constrained to an extremely small fixed range through a dynamic window boundary strategy, thereby improving computational efficiency and avoiding geometric offsets caused by long-arc fitting. The adaptability and positioning accuracy of the proposed method were rigorously validated using multiple satellite altimetry datasets. The results indicate that the computational efficiency of the DWCC algorithm is improved by at least 50% compared with the traditional piecewise fitting method. In terms of positioning accuracy, the geometric offset and missing point issues are effectively overcome, and precise crossover point positioning is achieved. In MSS(mean sea surface) modeling experiment, the crossover results computed by the DWCC algorithm are found to be highly consistent with the SDUST2020 and CLS15 MSS models. Among all datasets, the Jason-1 GM data are shown to achieve the highest accuracy, with RMSE(root mean square error) better than 0.08 m. The relatively larger RMSE values of CryoSat-2 and Sentinel-3A are confirmed to be caused by systematic differences in geometric datums rather than by algorithm errors. Therefore, the DWCC algorithm is demonstrated to significantly improve computational efficiency while maintaining high accuracy, providing an efficient and reliable technical means for the precise acquisition of sea surface height.