This paper addresses the complexities of path planning in cooperative operations involving manned and unmanned aerial vehicles （MUAVs） and the limitations of traditional methods in dynamic environments. It presents an integrated approach that incorporates an enhanced DWA （dynamic window approach） and Dijkstra's algorithm. By optimizing the trajectory evaluation function， the method efficiently avoids dynamic obstacles， ensuring optimal path planning within mission time constraints for MUAV teams. Simulation experiments demonstrate that the proposed method significantly improves the effectiveness of path optimization in complex and dynamic battlefield environments. Moreover， it strengthens the generalization and robustness of path planning across various scenarios.