Self-Tuning Weighted Measurement Fusion Kalman Signal Filter

Wen Qiang Liu; Gui Li Tao; Ze Yuan Gu; Song Li

doi:10.4028/www.scientific.net/AMM.274.579

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 274Self-Tuning Weighted Measurement Fusion Kalman...

Self-Tuning Weighted Measurement Fusion Kalman Signal Filter

Abstract:

For the single channel autoregressive moving average (ARMA) signals with multisensor and a colored measurement noise, when the model parameters and noise variances are partially unknown, based on identification method and Gevers-Wouters algorithm with a dead band, a self-tuning weighted measurement fusion Kalman signal filter is presented. A simulation example applied to signal processing shows its effectiveness.

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Periodical:

Applied Mechanics and Materials (Volume 274)

Pages:

579-582

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.274.579

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Online since:

January 2013

Authors:

Wen Qiang Liu, Gui Li Tao, Ze Yuan Gu, Song Li

Keywords:

ARMA Signals, Identification, Measurement Fusion, Multisensor Information Fusion

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References

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