[目的] 为解决复杂环境下海上无人系统时间协同航迹规划问题，[方法]建立了空中、海上和水下的自然环境和敌方威胁建立模型，构建了多约束条件下的航迹规划目标函数，提出一种时间协同策略，该策略解决了异构平台出发不同时不同地但到达同时同地的约束条件下的时间协同问题，采用DE(Differential Evolution)算法进行优化求解，并研究航点数量对规划成功率的影响。[结果]在合理选择航点个数的基础上，DE算法可在多威胁多障碍的复杂环境中为海上无人系统规划出满足时间协同约束的航迹，并使到达目标的时间最短。航点数量过多或过少将降低规划成功率。[结论]构建的模型和约束条件合理，使用的算法能够解决海上无人系统离线航迹规划时间协同问题，具有一定实用价值。
[Target] In order to solve the problem of time cooperative path planning for marine unmanned system in complex environment,[Methods] The models of air, sea and underwater natural environment and enemy threat are established. The objective function of path planning with multiple constraints is constructed. This strategy solves the problem of time cooperaiton when heterogeneous platforms start at different places but arrive at the same place at the same time .The DE are used to solve the problem，andthe influence of the number of waypoints on the success rate of planning is studed.[Results] On the basis of reasonable selection of the number of waypoints, DE algorithm can respectively plan the tracks satisfying the time cooperative constraint for the marine unmanned system, and make the time to reach the target shortest in the complex environment of multi threat and multi obstacle. Too many or too few waypoints will reduce the success rate of planning. [Conclusion]The model and constraint conditions are reasonable, and the algorithm can solve the problem of time coordination in the path planning of unmanned system at sea, which has the value of practical application.