Decentralized Estimation of Linear Gaussian Systems
MASSACHUSETTS INST OF TECH CAMBRIDGE LAB FOR INFORMATION AND DECISION SYSTEMS
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In this paper, we propose a framework for the design of linear decentralized estimation schemes based on a team-theoretic approach. We view local estimates as decisions which affect the information received by other decision makers. Using results from team theory, we provide necessary conditions for optimality of the estimates. For fully decentralized structures, these conditions provide a complete closed-form solution of the estimation problem. The complexity of the resulting estimation algorithms is studied as a function of the performance measure, and in the context of some simple examples.
- Statistics and Probability