This note defines the problem of least-squares dis- tributed estimation from relative and absolute measurements, by encoding the set of measurements in a weighted undirected graph. The role of its topology is studied by an electrical interpretation, which easily allows distinguishing between topologies that lead to “small” or “large” estimation errors. The least-squares problem is solved by a distributed gradient algorithm: the computed solution is approximately optimal after a number of steps that does not depend on the size of the problem or on the graph- theoretic properties of its encoding. This fact indicates that only a limited cooperation between the sensors is necessary.

Distributed Estimation from Relative and Absolute Measurements / Rossi, W. S.; Frasca, P.; Fagnani, F.. - In: IEEE TRANSACTIONS ON AUTOMATIC CONTROL. - ISSN 0018-9286. - STAMPA. - 62:12(2017), pp. 6385-6391. [10.1109/TAC.2017.2661400]

Distributed Estimation from Relative and Absolute Measurements

W. S. Rossi;P. Frasca;F. Fagnani
2017

Abstract

This note defines the problem of least-squares dis- tributed estimation from relative and absolute measurements, by encoding the set of measurements in a weighted undirected graph. The role of its topology is studied by an electrical interpretation, which easily allows distinguishing between topologies that lead to “small” or “large” estimation errors. The least-squares problem is solved by a distributed gradient algorithm: the computed solution is approximately optimal after a number of steps that does not depend on the size of the problem or on the graph- theoretic properties of its encoding. This fact indicates that only a limited cooperation between the sensors is necessary.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2702991
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