SENSOR FAULT DETECTION BY TESTING THE GENERALIZED VARIANCE OF THE INNOVATION COVARIANCE

Chingiz Hajiyev, Ulviye Hacizade
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:
sensor, fault detection, Kalman filter, innovation sequence, generalized variance
Download:
IMEKO-WC-2015-TC10-238.pdf
DOI:
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Event details
Event name:
XXI IMEKO World Congress
Title:

Measurement in Research and Industry

Place:
Prague, CZECH REPUBLIC
Time:
30 August 2015 - 04 September 2015
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