In order to solve the problem that traditional crossover positioning methods for massive multi-source satellite altimetry data struggle to balance accuracy and efficiency, a Dynamic Window Constrained Crossover (DWCC) Algorithm was used to investigate the data processing of marine gravity field inversion and mean sea surface (MSS) modeling. This method integrates spatial pre-screening with computer graphics logic to eliminate redundant calculations via a multi-level constraint mechanism. By employing a dynamic fixed-length window, it constrains the solution to a minimal range, enhancing efficiency and mitigating geometric offsets from long-arc fitting. Its adaptability and positioning accuracy have been rigorously validated through experiments across diverse satellite altimetry datasets. The results show that: the computational efficiency of DWCC is improved by at least 50% compared with the piecewise fitting method; in terms of positioning accuracy, DWCC effectively overcomes geometric offset and missing points, achieving close fitting with real trajectories. In the comparative analysis with SDUST2020 and CLS15 MSS models, DWCC maintains high consistency with reference models. Specifically, the Jason-1 GM data achieves the highest absolute accuracy with a root mean square error (RMSE) better than 0.08 m , while the larger RMSE of CryoSat-2 and Sentinel-3A is confirmed to be caused by systematic differences in geometric datums rather than algorithm errors. It is concluded that the DWCC algorithm significantly improves computational efficiency while ensuring high accuracy, providing a feasible technical means for precise sea surface height acquisition.