Stochastic Detectability and Mean Bounded Error Covariance of the Recursive Kalman Filter with Markov Jump Parameters

Autor(es)

Costa, Eduardo F. ^[1] ; Astolfi, Alessandro ^{[2, 3]}

Afiliação do(s) autor(es)

^[1] USP, ICMC, Dept Matemat Aplicada & Estat, BR-13560970 Sao Carlos, SP - Brazil

^[2] Univ Roma Tor Vergata, Dipartimento Informat Sistemi & Prod, Rome - Italy

^[3] Univ London Imperial Coll Sci Technol & Med, Dept Elect & Elect Engn, London - England

• Tipo de documento: Artigo Científico
• Fonte: Stochastic Analysis and Applications; v. 28, n. 2, p. 190-201, 2010.
• Citações Web of Science: 2

Resumo

In this article, we study the error covariance of the recursive Kalman filter when the parameters of the filter are driven by a Markov chain taking values in a countably infinite set. We do not assume ergodicity nor require the existence of limiting probabilities for the Markov chain. The error covariance matrix of the filter depends on the Markov state realizations, and hence forms a stochastic process. We show in a rather direct and comprehensive manner that this error covariance process is mean bounded under the standard stochastic detectability concept. Illustrative examples are included. (AU)

• Processo FAPESP: 06/04210-6 - Convergência do Filtro de Kalman para sistemas lineares com saltos markovianos com da variável de salto
• Beneficiário: Eduardo Fontoura Costa
• Modalidade de apoio: Auxílio à Pesquisa - Regular