Specific structures for large-scale state estimation algorithms having information exchange

This paper considers the design and evaluation of large-scale state estimation algorithms having specific structures which allow the subsystems to exchange information over noisy channels. The specific structures which are presented are first motivated by considering the relative performance between the surely locally unbiased filter and a global dynamics filter. The role of the surely locally unbiased filter in evaluating the tradeoffs between the cost of information transfer and filter performance is examined and a theorem is presented which forms the basis for an algorithm for calculating channel noise crossover levels. The theoretical results are illustrated via an application to a power system model.