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.