Data Fusion and Prediction for CBRN Transport and Dispersion for Security
Data Fusion and Prediction for CBRN Transport and Dispersion for Security
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CBRN 传输和扩散的数据融合和预测以确保安全
DOI：
10.1109/aero.2008.4526584
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
A. Annunzio
中科院分区：
文献类型：
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作者：
S. E. Haupt;G. Young;K. Long;A. Beyer;A. Annunzio
如果有毒污染物被释放到大气中，无论是事故还是恐怖活动，负责机构必须迅速查明污染源，预测污染物的路径和命运，警告公众或军事指挥部，并采取行动保护公众，军事人员和设备以及基础设施。如果不知道辐射源的位置和类型，如果没有密集的气象站网络，这一过程可能会很困难。然而，如果有污染物传感器，则可以使用基于遗传算法的软件包反算污染源和气象条件，并通过应用数据同化方法更好地预测污染物的运输和扩散。本文介绍了一种传感器数据融合/气象数据同化混合系统的开发技术。这项工作还分析了数据中噪声的影响，并评估了执行所需计算需要多少数据。
If a toxic contaminant is released in the atmosphere, either by accident or by terrorist activity, the responsible agency must rapidly identify the source, forecast the path and fate of the contaminant, warn the public or military command, and take action to protect the public, military personnel and equipment, and infrastructure. This process could be difficult if the location and type of source are not known and if there is not a dense network of meteorological stations. If, however, there are contaminant sensors, then the source and meteorological conditions can be back-calculated using a genetic algorithm-based software package and the transport and dispersion of the contaminant better predicted by applying data assimilation methods. This paper describes a technique for developing a sensor data fusion/meteorological data assimilation hybrid system. This work also analyzes the impact of noise in the data and assesses how much data are needed to perform the desired calculations.