A direct approach to identify the noise covariances of Kalman filtering

DOI10.1109/TAC.1980.1102411zbMath0445.93035OpenAlexW2018324091MaRDI QIDQ3890524

Tony T. Lee

Publication date: 1980

Published in: IEEE Transactions on Automatic Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1109/tac.1980.1102411

zbMATH Keywords

Kalman filterGaussian white noisescorrelation method

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Discrete-time control/observation systems (93C55) Estimation and detection in stochastic control theory (93E10) Linear systems in control theory (93C05)

Related Items (5)

Design of measurement difference autocovariance method for estimation of process and measurement noise covariances ⋮ Optimal and self-tuning white noise estimators with applications to deconvolution and filtering problems ⋮ Accurate derivative estimation from noisy data: a state-space approach ⋮ Optimal and self-tuning weighted measurement fusion Kalman filters and their asymptotic global optimality ⋮ Optimal and self-tuning weighted measurement fusion Wiener filter for the multisensor multichannel ARMA signals

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