论文部分内容阅读
多星协同观测可以最大化卫星的整体效能,如何对多星进行部署是一个设计空间大、设计变量多的优化问题。对此,提出了基于Kriging模型的改进广义模式搜索算法。在算法的搜索步,通过代理模型最优和最大期望提高在当前网格内进行选点,避免选择的盲目性;在筛选步,利用代理模型预测筛选集中各点提高的比例并排序,减少不必要的仿真分析。最后,采用该算法对多星部署方案进行优化,通过对比发现,算法性能优于STK-Analyzer,证明了算法的可行性和有效性。
Multi-satellite collaborative observation can maximize the overall efficiency of the satellite. How to deploy the multi-satellite is an optimization problem with large design space and large design variables. In this regard, an improved generalized pattern search algorithm based on Kriging model is proposed. In the search step of the algorithm, through the optimal and maximum expectation of the proxy model, the selection points in the current grid are avoided and the blindness of the selection is avoided. In the screening step, the agent model is used to predict the proportion of the points in the screening set to increase and sort to reduce Necessary simulation analysis. Finally, this algorithm is used to optimize the multi-satellite deployment scheme. The comparison shows that the performance of the algorithm is better than STK-Analyzer, which proves the feasibility and effectiveness of the algorithm.