Fault detection and isolation for sensor information fusion Kalman filter

Ali Okatan; Chingiz Hajiyev; Ulviyya Hajiyeva

doi:10.23919/ecc.2007.7068666

Fault detection and isolation for sensor information fusion Kalman filter

Ali Okatan, Chingiz Hajiyev, Ulviyya Hajiyeva

Department of Aeronautical Engineering

Halic University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

An approach to the test of the sensor information fusion Kalman filter is proposed. It is based on the introduced statistics of mathematical expectation of the spectral norm of a normalized innovation matrix. The approach allows for simultaneous test of the mathematical expectation and the variance of innovation sequence in real time and does not require a priori information on values of the change in its statistical characteristics under faults. Using this approach, algorithms for test and diagnosis of the sensor information fusion Kalman filter are developed.

Original language	English
Title of host publication	2007 European Control Conference, ECC 2007
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	415-421
Number of pages	7
ISBN (Electronic)	9783952417386
DOIs	https://doi.org/10.23919/ecc.2007.7068666
Publication status	Published - 2007
Event	2007 9th European Control Conference, ECC 2007 - Kos, Greece Duration: 2 Jul 2007 → 5 Jul 2007

Publication series

Name	2007 European Control Conference, ECC 2007

Conference

Conference	2007 9th European Control Conference, ECC 2007
Country/Territory	Greece
City	Kos
Period	2/07/07 → 5/07/07

Bibliographical note

Publisher Copyright:
© 2007 EUCA.

Keywords

Fault detection
Fault isolation
Kalman filters
Parallel algorithms
Sensor fusion

Access to Document

10.23919/ecc.2007.7068666

Cite this

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title = "Fault detection and isolation for sensor information fusion Kalman filter",

abstract = "An approach to the test of the sensor information fusion Kalman filter is proposed. It is based on the introduced statistics of mathematical expectation of the spectral norm of a normalized innovation matrix. The approach allows for simultaneous test of the mathematical expectation and the variance of innovation sequence in real time and does not require a priori information on values of the change in its statistical characteristics under faults. Using this approach, algorithms for test and diagnosis of the sensor information fusion Kalman filter are developed.",

keywords = "Fault detection, Fault isolation, Kalman filters, Parallel algorithms, Sensor fusion",

author = "Ali Okatan and Chingiz Hajiyev and Ulviyya Hajiyeva",

note = "Publisher Copyright: {\textcopyright} 2007 EUCA.; 2007 9th European Control Conference, ECC 2007 ; Conference date: 02-07-2007 Through 05-07-2007",

year = "2007",

doi = "10.23919/ecc.2007.7068666",

language = "English",

series = "2007 European Control Conference, ECC 2007",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "415--421",

booktitle = "2007 European Control Conference, ECC 2007",

address = "United States",

}

Okatan, A, Hajiyev, C & Hajiyeva, U 2007, Fault detection and isolation for sensor information fusion Kalman filter. in 2007 European Control Conference, ECC 2007., 7068666, 2007 European Control Conference, ECC 2007, Institute of Electrical and Electronics Engineers Inc., pp. 415-421, 2007 9th European Control Conference, ECC 2007, Kos, Greece, 2/07/07. https://doi.org/10.23919/ecc.2007.7068666

Fault detection and isolation for sensor information fusion Kalman filter. / Okatan, Ali; Hajiyev, Chingiz; Hajiyeva, Ulviyya.
2007 European Control Conference, ECC 2007. Institute of Electrical and Electronics Engineers Inc., 2007. p. 415-421 7068666 (2007 European Control Conference, ECC 2007).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Hajiyev, Chingiz

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AB - An approach to the test of the sensor information fusion Kalman filter is proposed. It is based on the introduced statistics of mathematical expectation of the spectral norm of a normalized innovation matrix. The approach allows for simultaneous test of the mathematical expectation and the variance of innovation sequence in real time and does not require a priori information on values of the change in its statistical characteristics under faults. Using this approach, algorithms for test and diagnosis of the sensor information fusion Kalman filter are developed.

KW - Fault detection

KW - Fault isolation

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KW - Parallel algorithms

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PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2007 9th European Control Conference, ECC 2007

Y2 - 2 July 2007 through 5 July 2007

ER -

Fault detection and isolation for sensor information fusion Kalman filter

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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