Sensor Integration And Data Fusion
Sensor Integration And Data Fusion
复制标题
传感器集成和数据融合
DOI：
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发表时间：
1990
期刊：
影响因子：
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通讯作者：
S. Thomopoulos
中科院分区：
文献类型：
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作者：
S. Thomopoulos
传感器集成和数据融合的问题得到解决。我们认为，在一个连贯的方式结合来自不同来源的信息的问题。我们假设在融合时，来自各种传感器的信息可以以不同的形式提供。例如，来自红外（IR）传感器的数据可以与测距雷达（RR）数据组合，并且进一步与视觉图像组合。在每种情况下，来自不同传感器的数据和信息以不同的格式呈现，这可能不直接兼容所有传感器。此外，可用信息可以是属性而不是动态测量的形式。提出了一种适应多种信息源的传感器集成和数据融合理论。数据（或更一般地，信息）融合可以在不同的级别上进行，如动态级别、属性级别和证据级别。所有不同的水平被认为是真实的世界数据融合问题的几个实际例子进行了讨论。
The problem of sensor integration and data fusion is addressed. We consider the problem of combining information from diversified sources in a coherent fashion. We assume that at the fusion, the information from various sensors may be available in different forms. For example, data from infrared (IR) sensors may be combined with range radar (RR) data, and further combined with visual images. In each case, the data and information from the different sensors are presented in a different format which may not be directly compatible for all sensors. Furthermore, the available information may be in the form of attributes and not dynamical measurements. A theory for sensor integration and data fusion that accommodates diversified sources of information is presented. Data (or, more generically, information) fusion may proceed at different levels, like the level of dynamics, the level of attributes, and the level of evidence. All different levels are considered and several practical examples of real world data fusion problems are discussed.