Sensor fault detection by testing the generalized variance of the innovation covariance

Chingiz Hajiyev; Ulviye Hacizade

Sensor fault detection by testing the generalized variance of the innovation covariance

Chingiz Hajiyev, Ulviye Hacizade

Department of Aeronautical Engineering

Halic University

Research output: Contribution to conference › Paper › peer-review

1 Citation (Scopus)

Abstract

A new method for testing the covariance matrix of the innovation sequence of the Kalman filter is proposed. The generalized variance (determinant) of the random Wishart matrix is used in this process as a monitoring statistic, and the testing problem is reduced to determination of the asymptotics for Wishart determinants. In the simulations, the longitudinal and lateral dynamics of the F-16 aircraft model is considered, and detection of sensor failures, which affect the covariance matrix of the innovation sequence, are examined.

Original language	English
Publication status	Published - 2015
Event	21st IMEKO World Congress on Measurement in Research and Industry - Prague, Czech Republic Duration: 30 Aug 2015 → 4 Sept 2015

Conference

Conference	21st IMEKO World Congress on Measurement in Research and Industry
Country/Territory	Czech Republic
City	Prague
Period	30/08/15 → 4/09/15

Keywords

Fault detection
Generalized variance
Innovation sequence
Kalman filter
Sensor

Cite this

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title = "Sensor fault detection by testing the generalized variance of the innovation covariance",

abstract = "A new method for testing the covariance matrix of the innovation sequence of the Kalman filter is proposed. The generalized variance (determinant) of the random Wishart matrix is used in this process as a monitoring statistic, and the testing problem is reduced to determination of the asymptotics for Wishart determinants. In the simulations, the longitudinal and lateral dynamics of the F-16 aircraft model is considered, and detection of sensor failures, which affect the covariance matrix of the innovation sequence, are examined.",

keywords = "Fault detection, Generalized variance, Innovation sequence, Kalman filter, Sensor",

author = "Chingiz Hajiyev and Ulviye Hacizade",

year = "2015",

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AU - Hajiyev, Chingiz

AU - Hacizade, Ulviye

PY - 2015

Y1 - 2015

N2 - A new method for testing the covariance matrix of the innovation sequence of the Kalman filter is proposed. The generalized variance (determinant) of the random Wishart matrix is used in this process as a monitoring statistic, and the testing problem is reduced to determination of the asymptotics for Wishart determinants. In the simulations, the longitudinal and lateral dynamics of the F-16 aircraft model is considered, and detection of sensor failures, which affect the covariance matrix of the innovation sequence, are examined.

AB - A new method for testing the covariance matrix of the innovation sequence of the Kalman filter is proposed. The generalized variance (determinant) of the random Wishart matrix is used in this process as a monitoring statistic, and the testing problem is reduced to determination of the asymptotics for Wishart determinants. In the simulations, the longitudinal and lateral dynamics of the F-16 aircraft model is considered, and detection of sensor failures, which affect the covariance matrix of the innovation sequence, are examined.

KW - Fault detection

KW - Generalized variance

KW - Innovation sequence

KW - Kalman filter

KW - Sensor

UR - http://www.scopus.com/inward/record.url?scp=84951048095&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:84951048095

T2 - 21st IMEKO World Congress on Measurement in Research and Industry

Y2 - 30 August 2015 through 4 September 2015

ER -

Sensor fault detection by testing the generalized variance of the innovation covariance

Abstract

Conference

Keywords

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