  Localization and tracking of moving nodes via network navigation gives rise
to a new paradigm, where nodes exploit both temporal and spatial cooperation to
infer their positions based on intra- and inter-node measurements. While such
cooperation can significantly improve the performance, it imposes intricate
information processing that impedes network design and operation. In this
paper, we establish a theoretical framework for cooperative network navigation
and determine the fundamental limits of navigation accuracy using equivalent
Fisher information analysis. We then introduce the notion of carry-over
information, and provide a geometrical interpretation of the navigation
information and its evolution in time. Our framework unifies the navigation
information obtained from temporal and spatial cooperation, leading to a deep
understanding of information evolution in the network and benefit of
cooperation.
