FDI using Multiple Parity Vectors for Redundant Inertial Sensors

This paper discusses fault detection, isolation, and accommodation (FDIA) problem of redundant sensors in inertial navigation systems (INS). The averaged parity vector (APV) method is suggested to improve the probability of correct isolation and reduce the numbers of false alarms and wrong isolation...

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Bibliographic Details
Published inEuropean journal of control Vol. 12; no. 4; pp. 437 - 449
Main Authors Yang, Cheol-Kwan, Shim, Duk-Sun
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 2006
Subjects
Accommodation
Fault Detection and Isolation
Inertial Sensors
Navigation Accuracy
Parity Vector
Fault Detection and Isolation
Parity Vector
Accommodation
Inertial Sensors
Navigation Accuracy
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Summary:This paper discusses fault detection, isolation, and accommodation (FDIA) problem of redundant sensors in inertial navigation systems (INS). The averaged parity vector (APV) method is suggested to improve the probability of correct isolation and reduce the numbers of false alarms and wrong isolation. The proposed method employs a new accommodation threshold based on the error covariance of an estimated variable, which is related to the navigation accuracy of INS. This accommodation threshold is also used as the fault detection threshold, so the APV algorithm detects only non-tolerable faults. Given a conditional probability of correct isolation, the minimum number of sample measurements is given with respect to fault size. Computer simulation and experimental results verify the validity of the proposed method.
ISSN:0947-3580
1435-5671
DOI:10.3166/ejc.12.437-449