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Dynamical reconfiguration strategy of a multi sensor data fusion algorithm based on Information Theory

机译:基于信息理论的多传感器数据融合算法的动态重新配置策略

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Autonomous vehicle board an increasing quantity of sensors such as GNSS receivers, road maps, LIDARs, to ensure a reliable localization function. This expanding number leads to abandon a classical centralised data fusion method and to adopt more complex architectures such as Distributed Data Fusion. In this paper, we propose an approach to detect faults of the different sensors in such configuration and to dynamically reconfigure the fusion method by using simple concepts of Information Theory. In order to detect faults, consistency is examined through a log likelihood ratio between the information innovation of each sensor. The current study illustrates the performance of the proposed fault detection algorithm and the pertinence of the dynamical reconfiguration of the multi-sensors data fusion. Experimental results, using data from antilock braking system sensors, a differential global positioning system receiver, and an accurate digital roadmap illustrate the performance of the proposed approach.
机译:自动车辆板越来越多的传感器,如GNSS接收器,路线图,楣,以确保可靠的本地化功能。此扩展号码导致放弃经典的集中数据融合方法,并采用更复杂的架构,例如分布式数据融合。在本文中,我们提出了一种在这种配置中检测不同传感器的故障的方法,并通过使用简单的信息理论概念动态重新配置融合方法。为了检测故障,通过每个传感器的信息创新之间的日志似然比检查一致性。目前的研究说明了所提出的故障检测算法的性能和多传感器数据融合的动态重新配置的性能。实验结果,使用来自防姑式制动系统传感器的数据,差动全球定位系统接收器和准确的数字路线图说明了所提出的方法的性能。

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