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Architecture Analysis and Demonstration of Distributed Data Fusion

机译:分布式数据融合的体系结构分析和演示

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摘要

Information and Data Fusion is a discipline that provides methods and techniques to build Observe-Orient-Decide-Act (OODA) capabilities for various applications. There are many ways in which these methods and techniques can be chosen to provide capabilities in each phase of the OODA decision making cycle, and there are different fusion architectures, i.e., ways these methods and techniques can be applied, grouped and integrated. How one chooses the most appropriate set of methods, techniques and fusion architecture for an application depends on a number of factors. Additional factors have to be considered in the case when decision making is performed through a collaboration of a number of fusion centres on a network, defined as Distributed Data Fusion, in the context of this lecture. This lecture describes the choices for fusion architectures, the factors leading to the selection of a fusion architecture, and proposes a model to help make these choices in the case of distributed data fusion.
机译:信息和数据融合是一门学科,提供了为各种应用程序构建面向观察的决定行为(OODA)功能的方法和技术。可以选择许多方法来选择这些方法和技术以提供在OODA决策周期的每个阶段中的功能,并且存在不同的融合体系结构,即可以应用,分组和集成这些方法和技术的方法。如何为应用程序选择最合适的方法,技术和融合体系结构取决于许多因素。在本课程中,当通过网络上多个融合中心的协作进行决策时,还必须考虑其他因素,这些网络被定义为“分布式数据融合”。本讲座描述了融合体系结构的选择,导致选择融合体系结构的因素,并提出了一个模型来帮助在分布式数据融合的情况下做出这些选择。

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