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In this paper, we consider linear networked estimation strategies using the results from structured systems theory. We are interested in estimating a linear dynamical system where the observations are distributed over a network of agents. In this context, we devise both state fusion and observation fusion strategies that guarantee a stable estimator. We assume global observability, i.e., given all...
In this paper, we consider distributed estimation for discrete-time, linear systems, with finite-time data fusion of agent measurements between each time-step of the dynamics. Prior work in this context is related to average-consensus, where either the data fusion is implemented for an infinite time (in general) to reach average-consensus, or under restricted observability requirements (one-step and/or...
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