Hierarchical probability models and Bayesian analysis of mine locations
Hierarchical probability models and Bayesian analysis of mine locations
复制标题
矿井位置的分层概率模型和贝叶斯分析
DOI：
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复制
发表时间：
2000
影响因子：
1.2
通讯作者：
A. Lawson
中科院分区：
文献类型：
--
作者：
N. Cressie;A. Lawson
根据对潜在雷场的遥感，确定点位置，其中一些可能不是地雷。地雷和类似地雷的物体是根据它们的点图案来区分的，但必须强调的是，人们所看到的只是它们位置的叠加。在本文中，我们构建了一个层次空间点过程模型，该模型考虑了地雷和类地雷物体的不同模式，并使用后验分析来区分它们。我们的贝叶斯方法应用于从多光谱视频遥感系统获得的雷场数据。
Based on remote sensing of a potential minefield, point locations are identified, some of which may not be mines. The mines and mine-like objects are to be distinguished based on their point patterns, although it must be emphasized that all one sees is the superposition of their locations. In this paper, we construct a hierarchical spatial point-process model that accounts for the different patterns of mines and mine-like objects and uses posterior analysis to distinguish between them. Our Bayesian approach is applied to minefield data obtained from a multispectral video remote-sensing system.