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A Software Framework for Heterogeneous, Distributed Data Fusion

In this paper we describe a software framework to enable heterogeneous, distributed data fusion of disparate information sources. The framework is agent-based and consists of three main elements. The first is a generalization of the target state to a container of arbitrary, uncertain attributes. The structure of this estimate can vary both across time and across different nodes in the same network. The second is the development of composable process and observation models. These make it possible to dynamically change the models at runtime to fit the current target state estimate