Distributed Receding Horizon Kalman Filter

Pepe Maestre Torreblanca, Pontus Giselsson, Anders Rantzer

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Sammanfattning

In this paper a distributed version of the Kalman filter is proposed. In particular, the estimation problem is reduced to the optimization of a cost function that depends on the system dynamics and the latest output measurements and state estimates which is distributed among the agents by means of dual decomposition. The techniques presented in the paper are applied to estimate the position of mobile agents.
Originalspråkengelska
Titel på värdpublikation49th IEEE Conference on Decision and Control (CDC)
DOI
StatusPublished - 2010
Evenemang49th IEEE Conference on Decision and Control - Atlanta, Georgia, USA
Varaktighet: 2010 dec. 15 → …

Konferens

Konferens49th IEEE Conference on Decision and Control
Land/TerritoriumUSA
OrtAtlanta, Georgia
Period2010/12/15 → …

Ämnesklassifikation (UKÄ)

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