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An Adaptive Kalman Filter Based on Sage Windowing Weights and Variance Components

Published online by Cambridge University Press:  13 May 2003

Yuanxi Yang  and
Tianhe Xu
Yuanxi Yang
Affiliation:
Xi'an Research Institute of Surveying and Mapping, P.R. China
Tianhe Xu
Affiliation:
Xi'an Research Institute of Surveying and Mapping, P.R. China
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Abstract

In this paper a brief review of Sage adaptive filtering is followed by an analysis of the shortcomings of covariance matrices formed by windowing residual vectors, innovation vectors and correction vectors of the dynamic states. A new adaptive Kalman filter is developed by combining the Sage filter and the variance components and its use tested against various other schemes.

Keywords

Sage filteringAdaptive estimationRobust estimationVariance components
Type
Research Article
Information
The Journal of Navigation , Volume 56 , Issue 2 , May 2003 , pp. 231 - 240
Copyright
© 2003 The Royal Institute of Navigation

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