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This work is an extension to a companion paper describing consensus-tracking for networked agents, and shows how those results can be applied to obtain least-squares fused estimates based on spatially distributed measurements. This mechanism is very robust to changes in the underlying network topology and performance, making it an interesting candidate for sensor fusion on autonomous mobile networks. We conclude with an example of a preliminary application to distributed Kalman Filtering using the proposed technique, illustrating the dependence of the performance on the structure of the underlying network.