Asymptotic distribution theory for the kalman filter state estimator

DOI10.1080/03610928408828808zbMath0555.62084OpenAlexW2018093813MaRDI QIDQ3218980

James C. Spall, Kent D. Wall

Publication date: 1984

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610928408828808

zbMATH Keywords

asymptotic normalitylinear discrete-time systemsstate space modelmodel validationnon-Gaussian disturbancesborderline stable-unstable systemsKalman filter state estimatormeasure of deviation from normalitystability properties of the state transition matrix

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Asymptotic distribution theory in statistics (62E20)

Related Items (9)

THE DISTRIBUTION OF NONSTATIONARY AUTOREGRESSIVE PROCESSES UNDER GENERAL NOISE CONDITIONS ⋮ Error-constrained finite-horizon tracking control with incomplete measurements and bounded noises ⋮ The Kantorovich inequality for error analysis of the Kalman filter with unknown noise distributions ⋮ Robust linearly constrained extended Kalman filter for mismatched nonlinear systems ⋮ An event-triggered approach to state estimation with multiple point- and set-valued measurements ⋮ Satellite conjunction analysis and the false confidence theorem ⋮ The Kalman-Lévy filter ⋮ Structural Electricity Models and Asymptotically Normal Estimators to Quantify Parameter Risk ⋮ An Adaptive Extended Kalman Filter with Application to Compartment Models

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• Rate of convergence in the two-dimensional limit theorem
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• Stochastic processes and filtering theory
• A Note on the Extraction of Components from Time Series
• Linear system identification from nonstationary cross-sectional data

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