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An experimental data fusion model for multisensor systems.

机译:用于多传感器系统的实验数据融合模型。

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The objective of this research is to develop a data fusion model for multiple sensor systems. This fusion model has the ability to fuse different types of information. It can associate data from multiple sensors to proper target in multi-target environment. The model recognizes and distinguishes between a static or a dynamic scene. Uncertainty management, which is one of the most difficult issues in data fusion systems, is conducted in this dissertation by employing a mathematical-based model called "Dempster-Shafer theory of evidence". Several applications of this fusion model are presented.
机译:这项研究的目的是为多传感器系统开发一个数据融合模型。该融合模型具有融合不同类型信息的能力。它可以将来自多个传感器的数据关联到多目标环境中的适当目标。该模型识别并区分静态或动态场景。本文通过采用称为“ Dempster-Shafer证据理论”的基于数学的模型来进行不确定性管理,这是数据融合系统中最困难的问题之一。介绍了该融合模型的几种应用。

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