Data fusion and prediction for CBRN transport and dispersion for security

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.