Multiscale Graphical Modeling in Space: Applications to Command and Control

Recently, a class of multiscale tree-structured models was introduced in terms of scale-recursive dynamics deened on trees. The main advantage of these models is their association with a fast, recursive, Kalman-lter prediction algorithm. In this article, we propose a more general class of multiscale graphical models over acyclic directed graphs, for use in command and control problems. Moreover, we derive the generalized-Kalman-lter algorithm for graphical Markov models, which can be used to obtain the optimal predictors and prediction variances for multiscale graphical models.