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Noise covariance matrices in state‐space models: A survey and comparison of estimation methods—Part I
Author(s) -
Duník Jindřich,
Straka Ondřej,
Kost Oliver,
Havlík Jindřich
Publication year - 2017
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2783
Subject(s) - covariance , matlab , noise (video) , covariance matrix , implementation , computer science , state space , focus (optics) , algorithm , space (punctuation) , mathematics , statistics , artificial intelligence , physics , optics , image (mathematics) , programming language , operating system
Summary This paper deals with the estimation of the noise covariance matrices of systems described by state‐space models. Stress is laid on the systematic survey and classification of both the recursive and batch processing methods proposed in the literature with a special focus on the correlation methods. Besides the correlation methods, representatives of other groups are introduced also with respect to their basic idea, estimate properties, assumptions and possible extensions, and user‐defined parameters. Common and dual properties of the methods are highlighted, and a simulation comparison using exemplary MATLAB implementations of the methods is provided.