By Topic

Suboptimal design of discrete Kalman filter and smoother with redundant measurements

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)
Yonezawa, K. ; Tsukuba Space Center, National Space Development Agency of Japan, Ibaraki, Japan

In applications, there exist numerous stochastic dynamic systems whose measurements are redundantly available. The algorithm of discrete Kalman filter and smoother generally requires a heavy computational load. Taking advantage of the measurement redundancy, the suboptimal design of the discrete Kalman filter, and smoother with redundant measurements are presented here to reduce computational load in time and storage.

Published in:

Automatic Control, IEEE Transactions on  (Volume:26 ,  Issue: 2 )