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The stability analysis of the adaptive two‐stage Kalman filter
Author(s) -
Kim Kwang Hoon,
Lee Jang Gyu,
Park Chan Gook
Publication year - 2007
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.950
Subject(s) - kalman filter , control theory (sociology) , alpha beta filter , ensemble kalman filter , fast kalman filter , stability (learning theory) , extended kalman filter , computer science , invariant extended kalman filter , adaptive filter , kernel adaptive filter , stage (stratigraphy) , filter (signal processing) , mathematics , moving horizon estimation , algorithm , artificial intelligence , filter design , computer vision , machine learning , control (management) , paleontology , biology
Recently, the adaptive two‐stage Kalman filter, which can track unknown random bias, was proposed. This filter can be used for systems with unknown random bias on the assumption that the stochastic information of a random bias is incomplete. This paper analyses the stability of the adaptive two‐stage Kalman filter. Copyright © 2007 John Wiley & Sons, Ltd.