By Topic

Information fusion Kalman filters with time-delayed 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

2 Author(s)
Sun Xiaojun ; Dept. of Autom., Heilongjiang Univ., Harbin ; Deng Zili

For the linear discrete time-invariant stochastic control systems with time-delayed measurements, they can be transformed into the systems without time-delayed measurements by introducing new measurement processes. Three distributed optimal information fusion Kalman filters weighted by matrices, diagonal matrices and scalars are presented in the linear minimum variance sense. They overcome the drawback that the augmented state method requires a large computational burden. They are locally optimal and are globally suboptimal. The accuracy of the fusers is higher than that of each local Kalman estimator. In order to compute the optimal weights, the formula of computing the cross-covariances among local smoothing errors is given. A Monte Carlo simulation example for the tracking system with time-delayed measurements and 3 sensors shows their effectiveness.

Published in:

Control Conference, 2008. CCC 2008. 27th Chinese

Date of Conference:

16-18 July 2008