时空谱多星协同任务规划算法研究

介绍了多星协同任务规划的重要性以及时空谱多星协同任务规划的优点,基于时间、空间和光谱协同观测约束优化模型,以金矿尾矿库污染、水资源污染和耕地荒漠化问题为例ꎬ分别在新疆伊犁河流域尾矿库区域、塔里木河流域和阿克苏区域随机生成观测任务,根据观测任务选取了多个成像卫星,通过仿真实验研究了基于启发式规则的贪婪算法、遗传算法、爬山算法对模型的求解效率和优化结果.验证了引入适宜度的必要性ꎬ以未观测点、任务适宜度、优先级、任务总价值为比较指标ꎬ综合分析和比较任务的总价值,验证了贪婪算法在本文模型中优于遗传算法和爬山算法.

Comparison of Spatio-temporal Spectrum Multi-satellite Collaborative Task Planning Algorithms

Introduces the importance of multi-satellite collaborative observation mission planning and the advantages of spatio-temporal spectrum multi-satellite collaborative task planning.Based on the time,space and spectral cooperative observation constrained optimization model,taking the gold mine tailings pond pollution,water resources pollution and cultivated land desertification as examples,the observation missions were randomly generated in the tailings reservoir area,the Tarim River basin and the Aksu area of the Yili River Basin in Xinjiang,and multiple imaging satellites were selected according to the observation mission.The efficiency and optimization results of the greedy algorithm,genetic algorithm and hill climbing algorithm based on heuristic rules are compared by simulation experiments.Based on the unobserved points,task suitability,priority,and total task value as the comparison indicators,the total value of the analysis and comparison tasks is comprehensively analyzed.It is verified that the greedy algorithm is superior to the genetic algorithm and the hill climbing algorithm in this model.