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Derivation of a bilinear Kalman filter with autocorrelated inputs

Title
Derivation of a bilinear Kalman filter with autocorrelated inputs
Type
Article in International Conference Proceedings Book
Year
2007
Authors
Ramos, MJ
(Author)
FCUP
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Conference proceedings International
Pages: 2634-2640
46th IEEE Conference on Decision and Control
New Orleans, LA, DEC 12-14, 2007
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Authenticus ID: P-004-EB9
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
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Article in International Conference Proceedings Book
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