通过分析多颗SAR卫星对某一大面积区域目标进行协同观测的约束条件，以给定任务周期内观测收益最大为目标函数，建立约束满足模型。为改善传统的禁忌搜索算法在多星协同观测任务中易收敛于局部最优解的问题，提出一种改进的变邻域禁忌搜索算法。在算法实现的过程中，将区域目标网格化从而动态生成观测模式，并计算各模式对应的观测率。相对于传统的禁忌搜索算法，该变邻域禁忌搜索算法在同等资源下可将观测收益提高8%以上。
郑起存
,
岳海霞
,
刘大成
,
李华
,
任明山
,
贾小雪
. 基于区域目标网格化的多星协同观测方法[J]. 中国科学院大学学报, 2024
, 41(6)
: 803
-809
.
DOI: 10.7523/j.ucas.2023.019
By analyzing the constraints of using multiple SAR satellites to observe a specific large area target, the constraint satisfaction model is established to maximize the observation profit within a given mission time horizon. To improve the global search capabilities of the traditional tabu search algorithm, an improved tabu search algorithm with the variable neighbourhood is proposed. In implementing the algorithm with variable neighbourhood, the area target is gridded to dynamically generate observation patterns, and the observation rates are calculated for each pattern. Compared to the traditional tabu search algorithm, the variable neighbourhood tabu search algorithm proposed in this paper increases the observation profit by more than 8% while maintaining the same computational burden.
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