Equivalence classes of future paths for sensor allocation and threat analysis

Abstract

Sensor allocation and threat analysis are difficult fusion problem that can sometimes be approximately solved using simulations of the future movement of adversary units. In addition to requiring detailed motion models, such simulation also requires large amounts of computational resources, since a large number of possibilities must be examined. In this paper, we extend our previously introduced framework for doing such simulations more efficiently. The framework is based on defining equivalence classes of future paths of a set of units. In the simplest case, two paths are considered equivalent if they give rise to the same set of observations. For sensor management, each considered sensor plan thus entails an equivalence relation on the set of future paths. This can be used to significantly reduce the number of "alternative futures" that need to be considered for the simulation. For threat analysis, the equivalence relation can instead be based on the perceived threat against own units. We describe how the equivalence classes induced by such relations could be used to improve the visualization of threat analysis systems. User interaction can also be used to refine the equivalence classes; we argue that such interaction will be essential for international operations where is it difficult to define actors and targets.