Title :
Distributed receding horizon Kalman filter
Author :
Maestre, J.M. ; Giselsson, P. ; Rantzer, A.
Author_Institution :
Dept. of Syst. & Autom. Eng., Univ. of Seville, Seville, Spain
Abstract :
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 local subsystems by means of dual decomposition. The techniques presented in the paper are applied to estimate the position of mobile agents.
Keywords :
Kalman filters; optimisation; state estimation; cost function; distributed receding horizon Kalman filter; dual decomposition; estimation problem; mobile agents; optimization; output measurements; state estimates; system dynamics; Cost function; Equations; Estimation; Kalman filters; Mathematical model; Trajectory;
Conference_Titel :
Decision and Control (CDC), 2010 49th IEEE Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-7745-6
DOI :
10.1109/CDC.2010.5717370
