在进行大规模遥感卫星体系论证时，针对单个用户部门、一星一议式的遥感卫星需求的传统分析方法已不再适用.为了解决这个问题，以光学遥感应用需求为研究对象提出一种遥感应用需求聚类算法.首先，通过需求指标分析提取出空间分辨率等5个体系级需求指标，以实现需求结构化表达；然后，构造基于需求满足度评估的相似性测度，并以需求满足度作为衡量需求间相似性的量化指标；最后，设计基于满足度测度的最大最小距离聚类算法，进而提取出中心类别需求.实验结果表明，该方法可以很好地合并同类需求，所得结果能支撑后续的体系设计与载荷研制工作.
When planning large-scale earth observation system, the traditional requirement analysis method, which just considers single user department and discusses satellite one by one, is no longer suitable. In order to solve this problem, this paper puts forward a kind of remote sensing application requirement clustering algorithm. First of all, through the analysis of the requirement criteria, we extract 5 systematical requirement criteria such as spatial resolution for the expression of structural requirements. Second, we establish requirement similarity definition based on satisfaction evaluation, and use it as a quantitative index to measure the similarity between requirements. Finally, we design the maximum and minimum distance clustering algorithms based on satisfaction degree to extract the center class requirements. The experimental results show that the method works well in merging similar requirements, and the clustering results will provide supports in earth observation system design and load development.
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