Self-Tuning Weighted Measurement Fusion Kalman Signal Filter

Self-Tuning Weighted Measurement Fusion Kalman Signal Filter

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...

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Veröffentlicht in:Applied Mechanics and Materials 2013-01, Vol.274, p.579-582
Hauptverfasser: Li, Song, Gu, Ze Yuan, Liu, Wen Qiang, Tao, Gui Li
Format: Artikel
Sprache:eng
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Zusammenfassung: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.
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.274.579