Cart (Loading....) | Create Account
Close category search window

A statistical index for sensor fault detection in sub-optimal navigation Kalman filters

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Kai-Yew Lum ; Temasek Labs., Nat. Univ. of Singapore, Singapore, Singapore

Many aerospace navigation systems rely on Kalman filters for sensor fusion and processing. In the case of the optimal filter, the innovation covariance is Gaussian, and sensor fault detection is classically achieved by statistical analysis of the normalized innovation sequence. This is less straight-forward in real-time testing especially in the case of a sub-optimal filter. This paper proposes a statistical approach for fault detection in sub-optimal Kalman filters, which is based on testing the expectation of a stochastic quadratic process suggested by Song and Speyer (1985). Upper- and lower bounds of this process can be obtained by some spectral property of filter characteristic matrices. For an exponentially convergent sub-optimal filter, the quadratic process is shown to be a supermartingale. Testing for violation of the martingale condition provides a means for fault detection. In real time, the approach requires statistics of the true error covariance, which can be estimated by the algorithm of Mehra (1972) using innovation statistics. The approach is illustrated in an example of barometer-aided INS vertical channel.

Published in:

Control Conference (ASCC), 2011 8th Asian

Date of Conference:

15-18 May 2011

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.