To address the altitude-constrained path planning problem for Unmanned Underwater Vehicles (UUVs) in complex terrain environments, this paper proposes an improved hybrid A^* path planning algorithm based on UUV motion characteristics, termed UUVA^*. Firstly, the traditional hybrid A^* algorithm is extended by expanding the state space and incorporating the nonholonomic motion constraints of UUVs. Secondly, motion primitives tailored to UUV navigation characteristics are designed, and the cost function is optimized to generate smoother and more navigable paths. Finally, to enhance search efficiency, a multi-resolution hierarchical search strategy and branch pruning mechanism are introduced, significantly reducing the number of node expansions. Simulation tests conducted in two representative complex terrains—submarine hills, and submarine canyons—verify the altitude-constrained planning capability of the proposed algorithm. Furthermore, comparative experiments against classical A^* algorithm, hybrid A^*, and RRT^* algorithms are conducted. The result shows that the generated paths are smoother and yield smaller tracking errors, making the proposed algorithm more suitable for practical UUV applications, which verifies the superior performance of the proposed method in terms of trajectory tracking error and path navigability.