CCE Faculty Articles
Derivation of a Bilinear Kalman Filter with Autocorrelated Inputs
Document Type
Article
Publication Title
IEEE Conference on Decision and Control
Event Date/Location
New Orleans, LA
ISSN
0191-2216
Publication Date
12-2007
Abstract
In this paper we derive a set of approximate but general bilinear Kalman filter equations for a multi- input multi-output bilinear stochastic system driven by general autocorrelated inputs. The derivation is based on a convergent Picard sequence of linear stochastic state-space subsystems. We also derive necessary and sufficient conditions for a steady-state solution to exist. Provided all the eigenvalues of a chain of structured matrices are inside the unit circle, the approximate bilinear Kalman filter equations converge to a stationary value. When the input is a zero-mean white noise process, the approximate bilinear Kalman filter equations coincide with those of the well known bilinear Kalman filter model operating under white noise inputs.
DOI
10.1109/CDC.2007.4434438
First Page
6196
Last Page
6202
NSUWorks Citation
Ramos, Jose A. and Lopes dos Santos, Paulo, "Derivation of a Bilinear Kalman Filter with Autocorrelated Inputs" (2007). CCE Faculty Articles. 397.
https://nsuworks.nova.edu/gscis_facarticles/397
