CEC Faculty Articles

Title

Derivation of a Bilinear Kalman Filter with Autocorrelated Inputs

Event Date/Location

New Orleans, LA

Document Type

Article

Date

12-2007

Publication Title

IEEE Conference on Decision and Control

ISSN or ISBN

0191-2216

First Page

6196

Last Page

6202

Description

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

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