Abstract: This talk will focus on the design of distributed estimation systems
that are formed by multiple non-collocated components. A shared network
is used to disseminate information among the components.
I will discuss two recent results: Assuming that the network is
characterized by an incomplete directed communication graph, the first
result characterizes the existence of omniscience-achieving schemes for
which all components that observe only a portion of the output of an
underlying plant can estimate the entire state with error that vanishes
asymptotically. Our approach hinges on key concepts from decentralized
control that are systematic and constructive. The second result
characterizes the structure of certain optimal policies for the case in
which the number of components exceeds the maximal number of
simultaneous transmissions that the network can accept. In order to
obtain a tractable framework for which design principles can be
characterized analytically, I will consider the case in which there are
two estimators that rely on information sent to them by two sensors that
access dissimilar measurements. I will show the optimality of certain
threshold-based policies, establish a connection with a problem of
optimal quantization for which the distortion is non-uniform across
representation symbols, present numerical approaches, discuss
interpretations of the results and list related open issues.
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