Derivation of a bilinear Kalman filter with autocorrelated inputs

• Type: Article in International Conference Proceedings Book
• Date: 2007

Authors

P. Lopes dos Santos (Author) FEUP; Ramos, MJ (Author) FCUP

Conference proceedings International

Title: PROCEEDINGS OF THE 46TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-14

Pages: 2634-2640

46th IEEE Conference on Decision and Control

New Orleans, LA, DEC 12-14, 2007

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Other information

Authenticus ID: P-004-EB9

DOI: 10.1109/cdc.2007.4434438

Abstract (EN): In this paper we derive a set of approximate but general bilinear Kalman filter equations for a multiinput 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7