Title :
Orthogonal state space decompositions with application to parallel filtering
Author :
Rhodes, Ian B. ; Luenberger, Robert A.
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA
Abstract :
A necessary and sufficient condition is given for the state space to be decomposable into a direct sum of mutually orthogonal observability subspaces. Such a decomposition has important consequences for the numerical conditioning of the basis changes that are involved in the implementation of an observer or Kalman filter as a collection of parallel subsystems
Keywords :
Kalman filters; filtering and prediction theory; observability; state estimation; Kalman filter; mutually orthogonal observability subspaces; observer; orthogonal state space decompositions; parallel filtering; state estimation; Application software; Artificial intelligence; Concurrent computing; Filtering; Matrix decomposition; Observability; State estimation; State-space methods; Sufficient conditions;
Conference_Titel :
Decision and Control, 1989., Proceedings of the 28th IEEE Conference on
Conference_Location :
Tampa, FL
DOI :
10.1109/CDC.1989.70641
