Robust Kalman filtering for continuous-time systems with norm-bounded nonlinear uncertainties (Q2703075)
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scientific article
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Robust Kalman filtering for continuous-time systems with norm-bounded nonlinear uncertainties |
scientific article |
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Robust Kalman filtering for continuous-time systems with norm-bounded nonlinear uncertainties (English)
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2 July 2001
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robust filtering
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nonlinear parameter uncertainties
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0.95938116
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0.95656943
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0.9555557
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0.95526737
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0.9536953
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0.95318156
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0.94934356
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0.9440874
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0.9434304
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The paper studies the filtering problem for continuous-time linear stochastic systems subject to state dependent parameter uncertainties satisfying a linear growth condition. The stability of such systems is analyzed and a suitable robust Kalman filter is proposed which guarantees a bounded covariance of the estimation error for all admissible uncertainties. The solution to the filtering problem is derived in terms of two algebraic Riccati equations. The paper is motivated by applications in target motion analysis, in particular the bearings-only tracking problem.
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