针对多卫星区域目标的成像规划问题，提出一种基于改进布谷鸟搜索的卫星成像规划方法。为最大限度地利用卫星资源，首先基于卫星的单次过境活动将区域目标按条带分解，然后考虑卫星姿态约束、传感器使用约束、过境时间约束、成像时云量及光照约束等，建立约束满足模型，针对模型设计编码和更新策略，并在布谷鸟搜索算法中引入非线性惯性权重对其进行改进，最后采用改进的布谷鸟搜索算法求解约束满足模型。求解结果表明，与遗传算法相比，本文算法的收敛性好、目标完成率高且稳定性强，验证了该算法的有效性。
This paper proposes a satellite mission planning method of multi-satellite regional targets based on improved cuckoo search(ICS) in order to maximize the use of satellite resources. Firstly, the regional target is decomposed into strips based on a single satellite transit activity. Secondly, the satellite attitude constraints, sensor usage constraints, transit time constraints, cloud cover and illumination constraints during imaging, etc. are considered to establish a constraint satisfaction model, for which coding and updating strategies are designed. Finally, an improved cuckoo search algorithm, with nonlinear inertia weight, is used to solve the constraint satisfaction model. The results of the experiment show that compared with genetic algorithm (GA), the proposed algorithm in this paper has better convergence, higher target completion rate and stronger stability, which proves the effectiveness of the method proposed in this paper.
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