A spatial-temporal statistical approach to problems in command and control
The integration, visualization, and overall management of battle-space information for the purpose of Command and Control (C2) is a challenging problem. For example, how can one assimilate incoming data rapidly in a highly dynamic environment, to allow the battle commander to make timely and informed decisions? In this paper, we present a spatial-temporal statistical approach to estimating the battlefield, based on noisy data from multiple sources. Specifically, we examine the dangerpotential field generated by an enemy's weapons in the spatial domain and extend it to incorporate the temporal dimension. We propose that maps of fields of this sort are very effective decision tools for the battle commander; methods for rapid updating of the maps is an area of current research. This includes visualization of the predictions and the uncertainty associated with them. It is the quantification of uncertainty in C2 predictions that distinguishes our statistical approach from deterministic approaches. In this paper we describe an object-oriented combat-simulation program from which we generate noisy battlefield data; in the absence of real data, we apply our methodology to these simulated data.