Finite-horizon Robust Kalman filter design

Minyue Fu; Carlos E. De Souza; Zhi Quan Tom Luo

doi:10.1109/78.942638

Finite-horizon Robust Kalman filter design

Minyue Fu
, Carlos E. De Souza
, Zhi Quan Tom Luo

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

113 Scopus citations

Abstract

In this paper, we study the problem of finite-horizon Kalman filtering for systems involving a norm-bounded uncertain block. A new technique is presented for robust Kalman filter design. This technique involves using multiple scaling parameters that can be optimized by solving a semidefinite program. The use of optimized scaling parameters leads to an improved design. A recursive design method that can be applied to real-time applications is also proposed.

Original language	English (US)
Pages (from-to)	2103-2112
Number of pages	10
Journal	IEEE Transactions on Signal Processing
Volume	49
Issue number	9
DOIs	https://doi.org/10.1109/78.942638
State	Published - Sep 2001

Keywords

Adaptive filtering
Kalman filtering
Robust filtering
Robust signal processing

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10.1109/78.942638

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abstract = "In this paper, we study the problem of finite-horizon Kalman filtering for systems involving a norm-bounded uncertain block. A new technique is presented for robust Kalman filter design. This technique involves using multiple scaling parameters that can be optimized by solving a semidefinite program. The use of optimized scaling parameters leads to an improved design. A recursive design method that can be applied to real-time applications is also proposed.",

keywords = "Adaptive filtering, Kalman filtering, Robust filtering, Robust signal processing",

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AB - In this paper, we study the problem of finite-horizon Kalman filtering for systems involving a norm-bounded uncertain block. A new technique is presented for robust Kalman filter design. This technique involves using multiple scaling parameters that can be optimized by solving a semidefinite program. The use of optimized scaling parameters leads to an improved design. A recursive design method that can be applied to real-time applications is also proposed.

KW - Adaptive filtering

KW - Kalman filtering

KW - Robust filtering

KW - Robust signal processing

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Finite-horizon Robust Kalman filter design

Abstract

Keywords

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